The ideal candidate will have a strong understanding of data warehousing fundamentals, SQL Server, and relational/dimensional database design. They will also possess excellent oral and written communication, presentation, and problem-solving skills. Experience working with large-scale data to build reporting solutions and knowledge of optimizing and performance tuning SQL and reports are highly desirable.

In addition to the above, the successful candidate will be a junior or senior in undergraduate studies, with a minimum of a bachelor's degree in a relevant field. They will be organized, positive, proactive, results-oriented, and able to work effectively in an open office/noisy environment.

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As a Senior HFT Developer on SPEED, you will design and build core low-latency components for order entry, market data, exchange simulation, feature extraction, and strategy containers, initially focused on delivering the full set of capabilities required for trading and research infrastructure. You will collaborate closely with system architects and quantitative researchers, operate and optimise these systems in production, and have clear opportunities to grow into technical and team leadership as the effort scales.

Principal Responsibilities:

• Build low-latency infrastructure for order entry, market data, exchange simulators, feature extraction, strategy container, and other systems.
• Build convenience layer tools and services to facilitate trading teams onboarding at MLP.
• Provide level 2 support for the systems in production.
• Work closely with the SPEED architect, quantitative researchers, and the business to provide high ROI solutions that are aligned with both the business and the platform strategy.
• Opportunities for growth in terms of leadership as effort expands.
• Will liaise with many other MLP teams depending on project focus.

Qualifications/Skills Required:

• 5+ years with a well-regarded HFT group, delivering production-grade, low-latency systems.
• Demonstrated expertise in C++ and Python for production, low-latency systems.
• Deep familiarity with low-level Systems: OS tuning, networking stack, user-space drivers, and kernel-bypass patterns.
• Strong understanding of the HFT quantitative research pipeline.
• Experience with HPC grids (scheduling, storage, job management) for research and production workloads.
• Cloud experience (AWS, GCP) is a plus.
• Proven ability to navigate large organisations, create cross-team synergies, and influence outcomes.
• High accountability and ownership; able to self-manage time, set priorities, and meet deadlines.
• Potential to provide technical leadership and manage a small team.

The estimated base salary range for this position is $175,000 to $250,000, which is specific to New York and may change in the future. We pay a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package.

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In this role, you'll collaborate with cross-functional teams to define, design, and deliver new features, proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. You'll present technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.

Ideally, you'd have 8+ years of full-time engineering experience, post-graduation, with specialties in back-end systems, specifically related to building large-scale data storage, streaming, and warehousing systems. You'll need extensive experience in various database technologies, streaming/processing solutions, indexing/caching, and various data query engines.

As a Staff Software Engineer, you'll provide technical leadership, including upholding and upleveling engineering standards across the organization, mentoring junior engineers. You'll possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.

Experience working fluently with standard containerization & deployment technologies like Kubernetes and various public cloud offerings is essential. You'll also need extensive experience in software development and a deep understanding of distributed systems, cloud platforms, and data systems.

You'll drive cross-functional collaboration and communication at an organizational or broader level, and be excited to work with AI technologies.

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Key Responsibilities:

• Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities.
• Design and experiment new approaches to preference optimization.
• Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness.
• Publish research findings in top-tier AI conferences.

Ideal Candidate:

• Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.
• Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.
• Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning.
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer-facing role.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

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You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimising the platform to enable our next generation LLM training, inference and data curation.

Key responsibilities include:

• Building, profiling and optimising our training and inference framework.
• Collaborating with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.
• Researching and integrating state-of-the-art technologies to optimise our ML system.

The ideal candidate will have:

• Passionate about system optimisation.
• Experience with multi-node LLM training and inference.
• Experience with developing large-scale distributed ML systems.
• Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
• Strong software engineering skills, proficient in frameworks and tools such as CUDA, PyTorch, transformers, flash attention, etc.

Nice to haves include demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

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At Scale AI, our mission is to accelerate the development of AI applications. This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents.

Responsibilities

• Explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation.
• Contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

Requirements

• Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow.
• A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.).
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.

Nice to Have

• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Benefits

• Comprehensive health, dental and vision coverage
• Retirement benefits
• A learning and development stipend
• Generous PTO
• Commuter stipend

Salary Range

$259,200-$324,000 USD

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Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality.

At Scale, we're uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale's ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation.

Responsibilities:

• Build, profile and optimize our training and inference framework
• Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation
• Research and integrate state-of-the-art technologies to optimize our ML system

Ideal Candidate:

• Strong excitement about system optimization
• Experience with multi-node LLM training and inference
• Experience with developing large-scale distributed ML systems
• Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
• Strong written and verbal communication skills and the ability to operate in a cross functional team environment

Nice to Have:

• Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.

Compensation Packages:

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please note that our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

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As a Staff+ Software Engineer, you will independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make architectural decisions that shape how Anthropic builds and scales its products. You will partner directly with research to productize cutting-edge capabilities, and will have lasting impact on the platform that hundreds of thousands of companies and internal/external engineers depend on every day.

Our team is responsible for Platform Acceleration, Service Infra, Multicloud, Auth & Identity, and Connectivity. We work on maximising developer productivity of product engineers at Anthropic, building and maintaining the core infrastructure that powers Anthropic's engineering organisation, operating across multiple cloud providers, and powering identity and authentication across Anthropic's product suite.

You will work on problems where reliability and enterprise trust are the bar: token refresh at scale, admin controls that let IT govern what agents can do, proxy infrastructure that stays up when partner servers don't. We ship for claude.ai, Claude Code, Cowork, and the API.

Relevant experience includes OAuth, API gateways, multi-tenant platforms, building for enterprise, and MCP.

We are looking for someone with 8-10+ years of practical full-stack engineering experience, ideally with 2+ years operating at a Staff or equivalent technical leadership level. You should have led the design and delivery of complex, consumer or B2B user-facing products across the full stack, and take a product-focused approach to building solutions that are robust, scalable, and easy to use.

Strong candidates may also have served as a technical lead or architect for a foundational platform system, owning both the technical vision and execution end-to-end, or experience designing or scaling billing, payments, or financial infrastructure at high transaction volumes.

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You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform.

You will continue to strengthen your technical skills through applying cutting-edge technologies in GenAI, MLOps, and ML more broadly, expanding your impact through mentorship, and establishing yourself as an AI thought leader.

The impact you will have:

• Architect production-level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimisation, integration with cloud-native services, MLOps, etc.

• Serve as trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems

• Build, scale, and optimise customer AI workloads and apply best-in-class MLOps to productionise these workloads across a variety of domains

• Provide advanced technical support to Solution Architects during the technical sale ranging from feature engineering, training, tracking, serving to model monitoring all within a single platform, as well as participating in the larger ML SME community in Databricks

• Collaborate cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities and influence the product roadmap, helping with the adoption of Databricks' AI offerings

What we look for:

• 5+ years of hands-on industry ML experience in at least one of the following:

• ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.

• AI Engineer: Experience with the latest techniques in LLMs & agentic systems including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI

• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience

• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike

• Passion for collaboration, life-long learning, and driving business value through ML & AI

• [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role

• Can meet expectations for technical training and role-specific outcomes within 3 months of hire

• This role can be remote, but we prefer that you be located in the job listing area and can travel up to 30% when needed

Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilising the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $219,100-$301,300 USD

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At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.

We're the only company offering three integrated solutions for frontier AI development:

• Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale

• Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models

• Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling

Why Join Us

• High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions.

• Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.

• Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.

• Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI.

• Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.

Role Overview

We’re looking for a Full-Stack AI Engineer to join our team, where you’ll build the next generation of tools for developing, evaluating, and training state-of-the-art AI systems. You will own features end to end,from user-facing experiences and APIs to backend services, data models, and infrastructure.

You’ll be at the heart of our applied AI efforts, with a particular focus on human-in-the-loop systems used to generate high-quality training data for Large Language Models (LLMs) and AI agents. This includes building a platform that enables us and our customers to create and evaluate data, as well as systems that leverage LLMs to assist with reviewing, scoring, and improving human submissions.

Your Impact

• Own End-to-End Product Features

Design, build, and ship complete workflows spanning frontend UI, APIs, backend services, databases, and production infrastructure.

• Enable Human-in-the-Loop AI Training

Build systems that allow humans to efficiently create, review, and curate high-quality training and evaluation data used in AI model development.

• Support RLHF and Preference Data Workflows

Design and implement tooling that supports RLHF-style pipelines, including task generation, human review, scoring, aggregation, and dataset versioning.

• Leverage LLMs in the Review Loop

Build systems that use LLMs to assist human reviewers,such as automated checks, critiques, ranking suggestions, or quality signals,while maintaining human oversight.

• Advance AI Evaluation

Design and implement evaluation frameworks and interactive tools for LLMs and AI agents across multiple data modalities (text, images, audio, video).

• Create Intuitive, Reviewer-Focused Interfaces

Build thoughtful, efficient user interfaces (e.g., in React) optimized for high-throughput human review, quality control, and operational workflows.

• Architect Scalable Data & Service Layers

Design APIs, backend services, and data schemas that support large-scale data creation, review, and iteration with strong guarantees around correctness and traceability.

• Solve Ambiguous, Real-World Problems

Translate loosely defined operational and research needs into practical, scalable, end-to-end systems.

• Ensure System Reliability

Participate in on-call rotations to monitor, troubleshoot, and resolve issues across the full stack.

• Elevate the Team

Improve engineering practices, development processes, and documentation. Share knowledge through technical writing and design discussions.

What You Bring

• Bachelor’s degree in Computer Science, Data Engineering, or a related field.

• 2+ years of experience in a software or machine learning engineering role.

• A proactive, product-focused mindset and a high degree of ownership, with a passion for building solutions that empower users.

• Experience using frontend frameworks like React/Redux and backend systems and technologies like Python, Java, GraphQL; familiarity with NodeJS and NestJS is a plus.

• Knowledge of designing and managing scalable database systems, including relational databases (e.g., PostgreSQL, MySQL), NoSQL stores (e.g., MongoDB, Cassandra), and cloud-native solutions (e.g., Google Spanner, AWS DynamoDB).

• Familiarity with cloud infrastructure like GCP (GCS, PubSub) and containerization (Kubernetes) is a plus.

• Excellent communication and collaboration skills.

• High proficiency in leveraging AI tools for daily development (e.g., Cursor, GitHub Copilot).

• Comfort and enthusiasm for working in a fast-paced, agile environment where rapid problem-solving is key.

Bonus Points

• Experience building tools for AI/ML applications, particularly for data annotation, monitoring, or agent evaluation.

• Familiarity with data infrastructure components such as data pipelines, streaming systems, and storage architectures (e.g., Cloud Buckets, Key-Value Stores).

• Previous experience with search engines (e.g., ElasticSearch).

• Experience in optimizing databases for performance (e.g., schema design, indexing, query tuning) and integrating them with broader data workflows.

Engineering at Labelbox

At Labelbox Engineering, we're building a comprehensive platform that powers the future of AI development. Our team combines deep technical expertise with a passion for innovation, working at the intersection of AI infrastructure, data systems, and user experience. We believe in pushing technical boundaries while maintaining high standards of code quality and system reliability. Our engineering culture emphasizes autonomous decision-making, rapid iteration, and collaborative problem-solving. We've cultivated an environment where engineers can take ownership of significant challenges, experiment with cutting-edge technologies, and see their solutions directly impact how leading AI labs and enterprises build the next generation of AI systems.

Our Technology Stack

Our engineering team works with a modern tech stack designed for scalability, performance, and developer efficiency:

• Frontend: React.js with Redux, TypeScript

• Backend: Node.js, TypeScript, Python, some Java & Kotlin

• APIs: GraphQL

• Cloud & Infrastructure: Google Cloud Platform (GCP), Kubernetes

• Databases: MySQL, Spanner, PostgreSQL

• Queueing / Streaming: Kafka, PubSub

Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.

Annual base salary range $130,000-$200,000 USD

Life at Labelbox

• Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland

• Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility

• Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making

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As a Research Scientist/Engineer focused on honesty within the Finetuning Alignment team, you'll spearhead the development of techniques to minimize hallucinations and enhance truthfulness in language models.

Your work will focus on creating robust systems that are accurate and reflect their true levels of confidence across all domains, and that work to avoid being deceptive or misleading.

Your work will be critical for ensuring our models maintain high standards of accuracy and honesty across diverse domains.

Responsibilities

• Design and implement novel data curation pipelines to identify, verify, and filter training data for accuracy given the model’s knowledge

• Develop specialized classifiers to detect potential hallucinations or miscalibrated claims made by the model

• Create and maintain comprehensive honesty benchmarks and evaluation frameworks

• Implement techniques to ground model outputs in verified information, such as search and retrieval-augmented generation (RAG) systems

• Design and deploy human feedback collection specifically for identifying and correcting miscalibrated responses

• Design and implement prompting pipelines to generate data that improves model accuracy and honesty

• Develop and test novel RL environments that reward truthful outputs and penalize fabricated claims

• Create tools to help human evaluators efficiently assess model outputs for accuracy

Requirements

• Have an MS/PhD in Computer Science, ML, or related field

• Possess strong programming skills in Python

• Have industry experience with language model finetuning and classifier training

• Show proficiency in experimental design and statistical analysis for measuring improvements in calibration and accuracy

• Care about AI safety and the accuracy and honesty of both current and future AI systems

• Have experience in data science or the creation and curation of datasets for finetuning LLMs

• An understanding of various metrics of uncertainty, calibration, and truthfulness in model outputs

Preferred qualifications

• Published work on hallucination prevention, factual grounding, or knowledge integration in language models

• Experience with fact-grounding techniques

• Background in developing confidence estimation or calibration methods for ML models

• A track record of creating and maintaining factual knowledge bases

• Familiarity with RLHF specifically applied to improving model truthfulness

• Worked with crowd-sourcing platforms and human feedback collection systems

• Experience developing evaluations of model accuracy or hallucinations

Benefits

• Competitive compensation and benefits

• Optional equity donation matching

• Generous vacation and parental leave

• Flexible working hours

• Lovely office space in which to collaborate with colleagues

Visa sponsorship

We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

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Your North Star: Build innovative, data-driven products that enhance patient engagement and retention to improve the lives of moms and babies.

We're looking to bring on an experienced Senior Data Scientist to own the data strategy for our Growth and Patient Experience team. In this role, you will hold a dual focus: optimizing the top-of-funnel strategy to grow patient enrollment, and driving the development of next-generation products that keep those patients engaged throughout their care journey.

Responsibilities

• Become an expert in patient behavior, engagement patterns, and retention drivers, owning the team’s data science roadmap and playing a foundational role in shaping Pomelo's patient experience strategy
• Collaborate deeply with the Marketing team to build and optimize a multi-channel enrollment strategy. You will build attribution models, analyze funnel conversion rates, and identify the best ways to allocate resources towards patient enrollment.
• Define and iterate on key metrics that define the health of the business, such as enrollment and retention rates, and present insights to Pomelo’s leadership team
• Complete exploratory analyses to inform development of enrollment and engagement-focused features, such as conversation topic categorization and patient journey segmentations
• Build robust data pipelines and analytics infrastructure that connect external, marketing and product usage data, creating a unified view of the patient journey.
• Lead the team’s approach to A/B testing across marketing and product initiatives to accurately measure impact
• Collaborate closely with Product, Clinical, and Engineering teams to translate patient insights into actionable product improvements and new feature development

Requirements

• 4+ years professional experience in data science, product analytics, or data engineering
• 1+ years professional experience working in healthcare, consumer health, or high-touch consumer products
• Expert proficiency in both SQL and Python, with demonstrated ability to work across the full data stack
• Strong product sense with experience in product prototyping, A/B testing, and user behavior analysis
• Passionate about improving maternal health outcomes and creating exceptional patient experiences
• Proven track record of scoping and implementing data-driven product solutions to complex, ambiguous problems
• Comfortable leading cross-functional initiatives with Product, Engineering, and Clinical teams as a strategic partner and technical expert
• A strong communicator and a keen nose for value - someone who can easily and quickly understand the needs of different audiences
• Experience with data visualization and dashboarding tools (e.g., Looker, Tableau, Metabase)
• Experience working with modern data stack tools (e.g., dbt, Airflow, Snowflake)

Bonus Points

• Experience with AI model development including fine-tuning, prompt engineering, model evaluation and building production AI applications
• Background in healthcare AI, clinical decision support, or medical NLP

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Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence.

The Role

In this role, you'll work with a team of elite researchers and engineers to design and implement post-training strategies that enhance Gemini’s capabilities in code security analysis. You will bring contributions to our ML innovation, post-training refinement (SFT/RLHF), advanced evaluation, and data generation to ensure our models can reliably perform safe and powerful code security analysis.

Key responsibilities:

• Design and Implement advanced post-training algorithms (SFT, RLHF, RLAIF) to optimize Gemini for code security tasks and secure coding practices.

• Diagnose and interpret training outcomes (regressions in coding ability, gains in security reasoning), and propose solutions to improve model capabilities.

• Actively monitor and evolve the system's performance through metric design.

• Develop reliable automated evaluation pipelines for code security that are strongly correlated with human security expert judgment.

• Construct complex benchmarks to probe the limits of the model’s ability to reason about control flow, memory safety, and software weakness.

About You

We are seeking individuals who excel in fast-pacing environments and are eager to contribute to the advancement of AI. We highly value the ability to invent novel solutions to complex problems, embracing a can-do and fail-fast mindset. We are looking for someone who genuinely believes in the future of AI and is committed to devoting their energy in this field.

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• BSc, MSc or PhD/DPhil degree in computer science, stats, machine learning or similar experience working in industry

• Deep understanding of statistics is strongly preferred

• Experiences in fine-tuning and adaptation of LLMs (e.g. advanced prompting, supervised fine-tuning, RLHF)

• Strong knowledge of systems design and data structures

• Proven experience with TensorFlow, JAX, PyTorch, or similar leading deep learning frameworks

• Recent experience conducting applied research to improve the quality and training/serving efficiency of large transformer-based models

• A passion for Artificial Intelligence.

• Excellent communication skills and proven interpersonal skills, with a track record of effective collaboration with cross-functional teams

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This role is perfect for an engineer who enjoys working close to the metal and across the research boundary. You'll collaborate with researchers and systems architects to bridge algorithmic design with hardware efficiency. You'll prototype new kernel implementations, profile performance across hardware generations, and help define the numerical and parallelism strategies that determine how we scale next-generation AI systems.

Responsibilities

• Design and implement custom ML kernels (e.g., CUDA, CuTe, Triton) for core LLM operations such as attention, matrix multiplication, gating, and normalization, optimized for modern GPU and accelerator architectures.
• Design and think through compute primitives to reduce memory bandwidth bottlenecks and improve kernel compute efficiency.
• Collaborate with research teams to align kernel-level optimizations with model architecture and algorithmic goals.
• Develop and maintain a library of reusable kernels and performance benchmarks that serve as the foundation for internal model training.
• Contribute to infrastructure stability and scalability, ensuring reproducibility, consistency across precision formats, and high utilization of compute resources.
• Document and share insights through internal talks, technical papers, or open-source contributions to strengthen the broader ML systems community.

Skills and Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar.
• Strong engineering skills, ability to contribute performant, maintainable code and debug in complex codebases
• Understanding of deep learning frameworks (e.g., PyTorch, JAX) and their underlying system architectures.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.
• Proficiency in CUDA, CuTe, Triton, or other GPU programming frameworks.
• Demonstrated ability to analyze, profile, and optimize compute-intensive workloads.

Preferred qualifications:

• Experience training or supporting large-scale language models with tens of billions of parameters or more.
• Track record of improving research productivity through infrastructure design or process improvements.
• Experience developing or tuning kernels for deep learning frameworks such as PyTorch, JAX, or custom accelerators.
• Familiarity with tensor parallelism, pipeline parallelism, or distributed data processing frameworks.
• Experience implementing low-precision formats (FP8, INT8, block floating point) or contributing to related compiler stacks (e.g., XLA, TVM).
• Contributions to open-source GPU, ML systems, or compiler optimization projects.
• Prior research or engineering experience in numerical optimization, communication-efficient training, or scalable AI infrastructure.

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Your expertise will be focused on the intricate details of system internals, performance, and efficiency. You will work closely with other senior engineers and architects to define technical strategies and roadmaps, and collaborate with junior engineers to mentor and contribute to a culture of technical excellence.

Responsibilities:

• Design, implement, and maintain core system infrastructure and low-level software components.
• Optimize system performance, reliability, and scalability through meticulous analysis and innovative solutions.
• Work with JVM internals, memory management, concurrency, and distributed systems.
• Collaborate with other senior engineers and architects to define technical strategies and roadmaps.
• Mentor junior engineers and contribute to a culture of technical excellence.
• Participate in code reviews, design discussions, and architectural decision-making.
• Troubleshoot complex system issues and provide effective resolutions.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
• 7+ years of professional experience in software development.
• Deep understanding of Java Virtual Machine (JVM) internals, including garbage collection, JIT compilation, class loading, and memory model.
• Proficiency in at least one JVM language and extensive experience with its runtime environment.
• Strong programming skills in Scala/Java/Rust or other systems-level languages.
• Extensive experience with operating system concepts; including processes, threads, concurrency, scheduling, and I/O.
• Proven track record of building and optimizing high-performance, scalable, and reliable systems.
• Experience with distributed systems concepts and technologies.
• Excellent problem-solving, analytical, and debugging skills.
• Strong communication and collaboration abilities
• Experience with performance profiling and tuning tools.
• Contributions to open-source projects related to JVM or systems software.
• Experience with RPC frameworks.

XML job scraping automation by YubHub

XML job scraping automation by YubHub

This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google and top customers.

You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest-generation models.

We are looking for engineers with a strong track record of building and shipping AI-powered software, ideally with experience in early-stage environments where they have contributed to scaling products from initial concept to production.

The ideal candidate will be motivated by the opportunity to drive product & business impact.

Key responsibilities:

• Harness frontier models to drive real-world high-impact outcomes

• Build evaluations, training data, and infrastructure to support AI deployments and rapid iterations

• Collaborate with researchers and product managers to translate research advancements into tangible product features.

• Contribute to the development of best practices for building and deploying generative AI applications.

• Contribute signal to influence the development of frontier models

• Lead the architecture and development of new products & features from 0 to 1.

About you:

In order to set you up for success as a Staff Research Engineer, Applied AI at Google DeepMind, we look for the following skills and experience:

Required Skills:

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development, and with data structures/algorithms.

• 5 years of hands-on experience in AI research (e.g. RL, finetuning, evals), AI applications, or model deployment

• Proven experience in rapidly developing and shipping software products.

• Deep understanding of software development best practices, including testing & deployment.

• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).

• Substantial experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.

• Ability to work in a fast-paced environment and adapt to changing priorities.

Preferred Skills:

• Experience with generative AI research or applications.

• Contributions to open-source projects.

• Experience working in, or founding early stage startups.

• Experience delivering software solutions in a fast-paced, customer-facing environment.

If you are a passionate machine learning engineer with a drive to build innovative products and a desire to work at the forefront of AI, we encourage you to apply!

The US base salary range for this full-time position is between $197,000 - $291,000 + bonus + equity + benefits.

XML job scraping automation by YubHub

You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform.

Your responsibilities will include:

• Architecting production-level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimization, integration with cloud-native services, MLOps, etc.

• Serving as a trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems

• Building, scaling, and optimizing customer AI workloads and applying best-in-class MLOps to productionize these workloads across a variety of domains

• Providing advanced technical support to Solution Architects during the technical sale ranging from feature engineering, training, tracking, serving to model monitoring all within a single platform, as well as participating in the larger ML SME community in Databricks

• Collaborating cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities and influence the product roadmap, helping with the adoption of Databricks' AI offerings

We are looking for someone with 5+ years of hands-on industry ML experience in at least one of the following areas:

• ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.

• AI Engineer: Experience with the latest techniques in LLMs & agentic systems including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI

A graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience is also required.

Additionally, experience communicating and/or teaching technical concepts to non-technical and technical audiences alike is highly valued.

The salary range for this position is $180,000-$247,500 USD, depending on location.

XML job scraping automation by YubHub

You'll perform penetration testing, conduct threat modeling, and provide guidance to engineering teams on secure design and best practices. This role also involves developing security tooling, researching emerging threats, and contributing to the continuous improvement of CoreWeave's overall security posture.

Some of what you'll work on:

• Perform penetration testing as well as purple and red team exercises.
• Conduct threat modeling, code reviews, and design reviews for development teams.
• Research new attack techniques and develop strategies to counter them.
• Develop and enforce security best practices and standards, maintaining internal compliance.
• Provide solutions to complex security issues, manage multiple tasks, and prioritize effectively in a fast-paced environment.
• Present technical security information to both technical and non-technical audiences.
• Maintain technical documentation, reports, and security tooling with attention to detail.
• Participate in other security-related initiatives as assigned.

Who You Are:

• 5+ years of experience in offensive information security roles.
• Proficiency in at least one programming or scripting language (e.g., Go, Python, C/C++) for automation, code reviews, and tooling.
• Hands-on penetration testing experience and familiarity with offensive security tools.
• Strong technical knowledge of Linux operating systems and containerized environments.
• Experience securing Kubernetes and understanding related security practices.
• Able to navigate ambiguity, identify root causes, and solve complex security problems.
• Excellent written and verbal communication skills with strong technical documentation abilities.
• Capable of working independently while managing multiple priorities in a fast-paced environment.
• Strong desire to continuously learn and adopt new technologies and security techniques.

Preferred:

• Experience with firmware reverse engineering, analyzing binaries, bootloaders, and embedded systems for vulnerabilities.
• Relevant certifications such as Sec+, Net+, OSCP, or equivalent.
• Experience with EDR tuning, detections-as-code, or threat hunting as part of a Blue Team.
• Deep understanding of business-wide security best practices and implementation strategies.

Wondering if you're a good fit?

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match.

Here are a few qualities we've found compatible with our team.

If some of this describes you, we'd love to talk.

• You love hunting vulnerabilities and proactively improving security.
• You're curious about evolving attack vectors and defense strategies.
• You're an expert in offensive security techniques and tooling, with a passion for safeguarding systems.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!

We're in an exciting stage of hyper-growth that you will not want to miss out on.

We're not afraid of a little chaos, and we're constantly learning.

Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking.

We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems.

As we get set for takeoff, the organization's growth opportunities are constantly expanding.

You will be surrounded by some of the best talent in the industry, who will want to learn from you, too.

Come join us!

The base salary range for this role is $165,000 to $242,000.

The starting salary will be determined based on job-related knowledge, skills, experience, and market location.

We strive for both market alignment and internal equity when determining compensation.

In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What We Offer

The range we've posted represents the typical compensation range for this role.

To determine actual compensation, we review the market rate for each candidate which can include a variety of factors.

These include qualifications, experience, interview performance, and location.

In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

• Medical, dental, and vision insurance
• 100% paid for by CoreWeave
• Company-paid Life Insurance
• Voluntary supplemental life insurance
• Short and long-term disability insurance
• Flexible Spending Account
• Health Savings Account
• Tuition Reimbursement
• Ability to Participate in Employee Stock Purchase Program (ESPP)
• Mental Wellness Benefits through Spring Health
• Family-Forming support provided by Carrot
• Paid Parental Leave
• Flexible, full-service childcare support with Kinside
• 401(k) with a generous employer match
• Flexible PTO
• Catered lunch each day in our office and data center locations
• A casual work environment
• A work culture focused on innovative disruption

Our Workplace

While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets.

New hires will be invited to attend onboarding at one of our hubs within their first month.

Teams also gather quarterly to support collaboration.

California Consumer Privacy Act - California applicants only

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace.

All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship.

If reasonable accommodation is needed, please contact: careers@coreweave.com.

Export Control Compliance

This position requires access to export controlled information.

To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the information under an appropriate export license, or (C) otherwise exempt from the regulations.

Applicant must also comply with all applicable laws and regulations related to the handling and transfer of export-controlled information.

By applying for this position, applicant acknowledges that they have read, understand, and will comply with these requirements.

Failure to comply with these requirements may result in termination of employment, revocation of any security clearances, or other disciplinary action.

Applicant must also agree to undergo a background investigation and obtain any necessary security clearances prior to commencing employment.

Please note that this position is subject to U.S. Government export regulations and may require applicant to sign a non-disclosure agreement (NDA) prior to commencing employment.

Applicant must also agree to comply with all applicable laws and regulations related to the handling and transfer of export-controlled information.

By applying for this position, applicant acknowledges that they have read, understand, and will comply with these requirements.

Failure to comply with these requirements may result in termination of employment, revocation of any security clearances, or other disciplinary action.

Applicant must also agree to undergo a background investigation and obtain any necessary security clearances prior to commencing employment.

Please note that this position is subject to U.S. Government export regulations and may require applicant to sign a non-disclosure agreement (NDA) prior to commencing employment.

XML job scraping automation by YubHub

You'll architect and implement our next-generation authorization infrastructure, including policy-as-code approaches, fine-grained permissions, and performance optimizations at massive scale, enabling GitLab's move toward zero-trust architecture while keeping authorization fast, secure, and correct.

You'll work closely with Security, Database, Platform, and authentication-focused teams to design and ship authorization capabilities that span GitLab's various deployment models and multi-tenant environments.

Some examples of our projects:

• Implementing fine-grained permissions for Job Tokens, Personal Access Tokens, and the GitLab Duo agent platform

• Collaborating on Auth stack initiatives that evolve how authorization works across GitLab

• Implement fine-grained permission systems for Job Tokens, Personal Access Tokens, the GitLab Duo Agent Platform, and other authentication mechanisms across the GitLab platform.

• Collaborate with Security, Authentication, Database, and Platform teams on authorization stack initiatives, aligning designs and implementation plans.

• Solve complex performance challenges in authorization, including query optimization, caching strategies, and database decomposition, with a focus on PostgreSQL.

• Design and evolve authorization systems that work across multiple deployment models and multi-tenant architectures while maintaining security and reliability.

• Drive improvements to authorization security, maintainability, and developer experience through code review, documentation, and technical leadership.

• Contribute to architectural decisions for authorization features with a long-term strategic view, balancing immediate needs with future scalability.

• Mentor and support other engineers in authorization patterns, policy-based access control, and secure coding practices in a fully remote, asynchronous environment.

• Professional experience building and maintaining production applications with Ruby on Rails or similar backend frameworks.

• Strong understanding of authorization models, including role-based access control, attribute-based access control, and fine-grained permission patterns.

• Experience designing and optimizing high-scale backend systems, including PostgreSQL performance tuning, query optimization, and effective caching strategies.

• Familiarity with or interest in policy-based authorization systems and modern policy languages such as Cedar or Rego.

• Understanding of core security principles, including threat modeling, least-privilege access, and zero-trust architectures.

• Experience working with distributed systems and service-to-service communication in a cloud or multi-tenant environment.

• Demonstrated ability to own complex technical initiatives from design through production deployment in an asynchronous, remote setting.

• Strong collaboration and communication skills, with openness to learning and applying transferable skills from adjacent domains or technologies.

We on the Authorization team at GitLab design, build, and maintain the permission systems that control access across the GitLab platform, ensuring they are secure, scalable, and flexible for customers of all sizes.

We lead the ongoing evolution of our authorization architecture, with a focus on modern policy-as-code approaches, fine-grained access control, and support for initiatives like the evolving Auth stack.

We collaborate asynchronously across time zones and partner closely with Authentication, Product Security, Database, and Security teams to align on identity, data modeling, and threat modeling needs while iterating safely on core platform capabilities.

How GitLab Supports Full-Time Employees:

• Benefits to support your health, finances, and well-being

• Flexible Paid Time Off

• Team Member Resource Groups

• Equity Compensation & Employee Stock Purchase Plan

• Growth and Development Fund

• Parental leave

• Home office support

XML job scraping automation by YubHub

At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.

As an Applied Research Engineer at Labelbox, you'll sit at the junction of advanced AI research and real product impact, with a focus on the data that makes modern agents work,browser interactions, SWE/code traces, GUI sessions, and multi-turn workflows. You'll drive the data landscape required to advance capable, adaptable agents and help shape Labelbox's strategy for collecting, synthesizing, and evaluating it.

Create frameworks and tools to construct, train, benchmark and evaluate autonomous agent capabilities.

Design agent-focused data programs using supervised fine-tuning (SFT) and reinforcement learning (RL) methodologies.

Develop data pipelines from diverse sources like code repositories, web browsers, and computer systems.

Implement and adapt popular open-source agent libraries and benchmarks with proprietary datasets and models.

Engage with research teams in frontier AI labs and the wider AI community to understand evolving agent data needs for frontier models and share best practices.

Collaborate closely with frontier AI lab customers to understand requirements and guide model development.

Publish research findings in academic journals, conferences, and blog posts.

What You Bring

Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or related field.

At least 3 years of experience addressing sophisticated ML problems with successful delivery to customers.

Experience building and training autonomous agents,tool use, structured outputs, multi-step planning,across browsers/GUI, codebases, and databases using SFT and RL.

Constructed and evaluated agentic benchmarks (e.g. SWE-bench, WebArena, τ-bench, OSWorld) and reliability/efficiency suites (e.g. WABER).

Adept at interpreting research literature and quickly turning new ideas into prototypes.

Deep understanding of frontier models (autoregressive, diffusion), post-training (SFT, RLVR, RLAIF, RLHF, et al.), and their human data requirements.

Proficient in Python, data science libraries and deep learning frameworks (e.g., PyTorch, JAX, TensorFlow).

Strong analytical and problem-solving abilities in ambiguous situations.

Excellent communication skills.

Track record of publications in top-tier AI/ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, etc.).

Labelbox Applied Research

At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios.

Life at Labelbox

Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland

Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility

Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making

Growth: Career advancement opportunities directly tied to your impact

Vision: Be part of building the foundation for humanity's most transformative technology

XML job scraping automation by YubHub

We're building a state-of-the-art Customer Data Platform, visualizing relevant insights for businesses post-onboarding and guiding customer engagement across all touch-points. Be part of the team that's redefining the way businesses connect with their customers!

Responsibilities:

• Design, implement, and maintain backend services and APIs to support applications.
• Build and optimize data storage solutions using Postgres, ClickHouse and Elasticsearch to ensure high performance and scalability.
• Collaborate with cross-functional teams, including frontend engineers, data scientists, and machine learning engineers, to deliver end-to-end solutions.
• Monitor and troubleshoot performance issues in distributed systems and databases.
• Write clean, maintainable, and efficient code following best practices for backend development.
• Participate in code reviews, testing, and continuous integration efforts.
• Ensure security, scalability, and reliability of backend services.
• Analyze and improve system architecture, focusing on performance bottlenecks, scaling, and security.

Qualifications We Value:

• Proven experience as a Backend Engineer with a focus on database design and system architecture.
• Strong expertise in ClickHouse or similar columnar databases for managing large-scale, real-time analytical queries.
• Hands-on experience with Elasticsearch for indexing and searching large datasets.
• Proficient in backend programming languages such as Python, Go.
• Experience with RESTful API design and development.
• Solid understanding of distributed systems, microservices architecture, and cloud infrastructure.
• Experience with performance tuning, data modeling, and query optimization.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.

XML job scraping automation by YubHub

Responsibilities:

• Design, implement, and maintain backend services and APIs to support applications.
• Build and optimize data storage solutions using Postgres, ClickHouse and Elasticsearch to ensure high performance and scalability.
• Collaborate with cross-functional teams, including frontend engineers, data scientists, and machine learning engineers, to deliver end-to-end solutions.
• Monitor and troubleshoot performance issues in distributed systems and databases.
• Write clean, maintainable, and efficient code following best practices for backend development.
• Participate in code reviews, testing, and continuous integration efforts.
• Ensure security, scalability, and reliability of backend services.
• Analyze and improve system architecture, focusing on performance bottlenecks, scaling, and security.

Qualifications We Value:

• Proven experience as a Backend Engineer with a focus on database design and system architecture.
• Strong expertise in ClickHouse or similar columnar databases for managing large-scale, real-time analytical queries.
• Hands-on experience with Elasticsearch for indexing and searching large datasets.
• Proficient in backend programming languages such as Python, Go.
• Experience with RESTful API design and development.
• Solid understanding of distributed systems, microservices architecture, and cloud infrastructure.
• Experience with performance tuning, data modeling, and query optimization.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.

XML job scraping automation by YubHub

Day-to-day, you’ll work on scaling infrastructure, improving deployment pipelines, and hardening our security posture. You’ll play a key role in evolving our DevSecOps practices while partnering closely with engineering teams to ensure services are built for reliability from day one.

We operate with production-grade discipline, supporting mission-critical services with stringent uptime requirements and a focus on automation, observability, and resilience.

The Platform & Infrastructure Engineering team in the Data Infrastructure organization is responsible for the reliability, scalability, and security of the company’s data platform. The team builds and operates the foundational systems that power data ingestion, transformation, analytics, and internal AI workloads at scale.

About the role:

• 5+ years of experience in Site Reliability Engineering, Platform Engineering, or Infrastructure Engineering roles
• Deep expertise in Kubernetes and containerized software services, including cluster design, operations, and troubleshooting in production environments
• Strong experience building and operating CI/CD systems, including tools such as Argo CD and GitHub Actions
• Proven experience owning production systems with high availability requirements (≥99.99% uptime), including incident response, SLI/SLO/SLA definition, error budgets, and postmortems
• Hands-on experience designing and operating geo-replicated, multi-region, active-active systems, including traffic routing, failover strategies, and data consistency tradeoffs
• Strong experience building and owning observability components, including metrics, logging, and tracing (e.g., Prometheus, Grafana, OpenTelemetry).
• Experience with infrastructure as code (e.g., Helm, Terraform, Pulumi) and automated environment provisioning
• Strong understanding of system performance tuning, capacity planning, and resource optimization in distributed systems
• Experience implementing and operating security best practices in cloud-native environments (e.g., secrets management, network policies, vulnerability scanning)

Preferred:

• Experience operating data platforms or data-intensive workloads (e.g., Spark, Airflow, Kafka, Flink)
• Familiarity with service mesh technologies (e.g., Istio, Linkerd)
• Experience working in regulated environments with compliance frameworks such as GDPR, SOC 2, HIPAA, or SOX
• Background in building internal developer platforms or self-service infrastructure

Wondering if you’re a good fit?

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren’t a 100% skill or experience match.

Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You love building highly reliable systems that operate at scale
• You’re curious about how to continuously improve system resilience, security, and operations
• You’re an expert in diagnosing and solving complex distributed systems problems

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning.

Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems.

As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too.

Come join us!

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation.

In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.

In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

• Medical, dental, and vision insurance
• 100% paid for by CoreWeave
• Company-paid Life Insurance
• Voluntary supplemental life insurance
• Short and long-term disability insurance
• Flexible Spending Account
• Health Savings Account
• Tuition Reimbursement
• Ability to Participate in Employee Stock Purchase Program (ESPP)
• Mental Wellness Benefits through Spring Health
• Family-Forming support provided by Carrot
• Paid Parental Leave
• Flexible, full-service childcare support with Kinside
• 401(k) with a generous employer match
• Flexible PTO
• Catered lunch each day in our office and data center locations
• A casual work environment
• A work culture focused on innovative disruption

Our Workplace

While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets.

New hires will be invited to attend onboarding at one of our hubs within their first month.

Teams also gather quarterly to support collaboration.

California Consumer Privacy Act - California applicants only

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace.

All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship.

If reasonable accommodation is needed, please contact: careers@coreweave.com.

Export Control Compliance

This position requires access to export controlled information.

To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without restrictions, or (C) otherwise exempt from the export regulations.

If you are not a U.S. person, you will be required to provide documentation of your eligibility to access the export controlled information before being considered for this position.

Please note that CoreWeave is subject to the requirements of the U.S. Department of Commerce's Export Administration Regulations (EAR) and the U.S. Department of State's International Traffic in Arms Regulations (ITAR).

By applying for this position, you acknowledge that you have read and understood the export control requirements and that you will comply with them.

If you have any questions or concerns regarding the export control requirements, please contact: careers@coreweave.com.

XML job scraping automation by YubHub

You will work on high-performance computing (HPC) systems that are part of our sequencing platform. The ideal candidate is a hands-on Linux expert who thrives on optimizing performance and building secure, scalable and reliable systems in a fast-paced environment.

Responsibilities:

• Design, build, and maintain high-performance Linux systems supporting compute and data-intensive workloads
• Optimise system performance through kernel and filesystem tuning; identify and eliminate I/O, memory, or network bottlenecks
• Automate provisioning and configuration management using orchestration tools such as Ansible and Salt
• Monitor and troubleshoot kernel, driver, and hardware issues; perform root cause analysis in partnership with data and engineering teams and propose long-term solutions
• Ensure system reliability through regular patching, monitoring, and performance tuning
• Maintain accurate system documentation, runbooks, and configuration baselines
• Collaborate with software, hardware, and scientific teams to ensure platform reliability and scalability

Qualifications, Skills, Knowledge & Abilities:

• BS in Computer Science, Engineering, or related field
• 5+ years of experience designing and building high-performance physical Linux systems in high-throughput or mission-critical environments
• Deep knowledge of Linux kernel, NFS and Linux file system performance tuning
• Solid background in TCP/IP networking, routing, VLANs, and firewall rules
• Experience with the latest CPU and GPU technologies
• Proficiency in shell scripting (bash), working knowledge of Python, and familiarity with Ansible or similar configuration management tools
• Proven hands-on experience building servers from components, diagnosing hardware failures, and working with vendors
• Excellent documentation and communication skills
• May occasionally be exposed to activity that requires pulling/lifting/moving/carrying up to 50 lbs
• Experience with cloud computing infrastructure (e.g. AWS) and Docker desirable
• Familiarity with security frameworks and compliance standards (e.g. ISO 27001) a plus

At Ultima Genomics, your base pay is one part of your total compensation package. This role pays between $125,000 and $150,000, if performed in California, and your actual base pay will depend on your skills, qualifications, experience, and location.

XML job scraping automation by YubHub

At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world's largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.

We protect and accelerate any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks.

About Role

We are looking for an experienced and highly motivated engineer to join our team and contribute to our analytical database platform. The platform is a critical component of Cloudflare Analytics which provides real-time visibility into the health and performance of Cloudflare customers' online properties.

The team builds and maintains a high-performance, scalable database platform powered by ClickHouse, optimized for analytical workloads. We help our customers, both internal and external, to gain a deeper understanding of their online properties, identify trends and patterns, and make informed decisions about how to optimize their web performance, security, and other key metrics.

Our mission is to empower customers to leverage their data to drive better outcomes for their business.

As a Distributed systems engineer - Analytical Database Platform, you will:

• Develop and implement new platform components for the Cloudflare Analytical Database Platform to improve functionality and performance.
• Add more database clusters to accommodate the growing volume of data generated by Cloudflare products and services.
• Monitor and maintain the performance and reliability of existing database platform clusters, and identify and troubleshoot any issues that may arise.
• Work to identify and remove bottlenecks within the analytics database platform, including optimizing query performance and streamlining data ingestion processes.
• Collaborate with the ClickHouse open-source community to add new features and functionality to the database, as well as contribute to the development of the upstream codebase.
• Collaborate with other teams across Cloudflare to understand their data needs and build solutions that empower them to make data-driven decisions.
• Participate in the development of the next generation of the database platform engine, including researching and evaluating new technologies and approaches that can improve the database's performance and scalability.

Key qualifications:

• 3+ years of experience working in software development covering distributed systems, and databases.
• Strong programming skills (Golang, python, C++ are preferable), as well as a deep understanding of software development best practices and principles.
• Strong knowledge of SQL and database internals, including experience with database design, optimization, and performance tuning.
• A solid foundation in computer science, including algorithms, data structures, distributed systems, and concurrency.
• Ability to work collaboratively in a team environment, as well as communicate effectively with other teams across Cloudflare.
• Strong analytical and problem-solving skills, as well as the ability to work independently and proactively identify and solve issues.
• Experience with ClickHouse is a plus.
• Experience with SALT or Terraform is a plus.
• Experience with Linux container technologies, such as Docker and Kubernetes, is a plus.

If you're passionate about building scalable and performant databases using cutting-edge technologies, and want to work with a world-class team of engineers, then we want to hear from you!

Join us in our mission to help build a better internet for everyone!

This role may require flexibility to be on-call outside of standard working hours to address technical issues as needed.

What Makes Cloudflare Special?

We're not just a highly ambitious, large-scale technology company. We're a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.

Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.

Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.

1.1.1.1: We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released.

Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers.

Sound like something you’d like to be a part of? We’d love to hear from you!

This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license.

Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at

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Your primary responsibilities will include designing, developing, and managing controls systems for manufacturing, architecting and writing PLC code, generating and enforcing internal standards for control systems architectures, and integrating internal and external FactoryOS software into automation equipment and production lines.

You will also lead root cause analysis and corrective actions for automation failures, install, configure, and tune servo drives/VFDs, and partner with cross-functional teams to troubleshoot equipment issues, reduce downtime, and drive continuous improvement initiatives.

To be successful in this role, you will need a bachelor's degree in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, or a similar field, and 8+ years of experience in controls and automation in a production environment. You should be proficient in PLC programming on both Rockwell and Siemens platforms, Ignition SCADA development, and servo drive and VFD configuration, PID tuning, STO/SS, etc.

Preferred qualifications include 10+ years of experience in controls and automation in a production environment, experience with control panel layout, electrical component selection, and cable routing, and familiarity with CAD packages including Solidworks, NX, CATIA, and AutoCAD.

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In this role, you will have the opportunity to work on cutting-edge projects, collaborate with a talented team of engineers and researchers, and contribute to the development of impactful technologies. You will also have access to a comprehensive benefits package, including healthcare benefits, income protection, generous time off, and professional development opportunities.

The ideal candidate will have a BS in Computer Science, Machine Learning, Electrical Engineering, or a related field, and 5+ years of experience developing and benchmarking ML algorithms. You will have strong Python skills with experience in ML frameworks such as PyTorch, and be eligible to obtain and maintain an active U.S. Secret security clearance.

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You'll be working closely with our Design team to evolve and scale our component library, ensuring it's accessible, composable, and well-documented. You'll also be responsible for profiling, diagnosing, and fixing client-side performance bottlenecks, establishing performance budgets, and building dashboards to keep the team honest.

As a force multiplier, you'll act as a coach and enablement specialist, helping product teams adopt improvements and level up their craft. You'll write playbooks and docs, deliver tech talks, pair with product engineers, and create local tooling to improve developer speed and quality.

In this role, you'll have the opportunity to work on a wide range of challenging projects, from performance optimization to design system evolution. You'll be part of a flat organizational structure, where everyone is valued and empowered to contribute. And, as a remote-friendly company, you'll have the flexibility to work from anywhere, with opportunities for in-person collaboration when needed.

If you're passionate about frontend platform work, enjoy making an entire engineering organization faster and more effective, and are excited about the prospect of joining a dynamic and growing company, we'd love to hear from you!

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The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb.

You will build and leverage cutting edge AI technologies to transform Airbnb’s customer service by delivering personalized, easy-to-use and proactive customer service experience.

A typical day involves envisioning, championing, and supporting the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems.

Your expertise should include a PhD/Master’s degree, preferably in CS, or equivalent experience, and 5-12 years of ML engineering experience, with ownership responsibility over large-scale software systems.

Experience with LLM driven chatbot and Agentic AI products would be a big plus.

Excellent communication skills and the ability to work well within a team and with teams across the engineering, product & design organizations are also required.

Fluency in both English and Mandarin is essential.

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In this role, you'll go beyond using AI tools and help define how we design, build, and iterate on AI-assisted and agentic CI experiences. You'll set standards for what good looks like across our AI agent portfolio, including how we measure success, how we instrument behavior in production, and how we account for large language model limitations. You'll also help responsibly integrate GitLab's Duo Agent Platform into CI workflows at scale, on a foundation that's fast, reliable, secure, and observable.

We have ambitious goals for Agentic CI in FY27. As a Staff Engineer, you will:

• Partner with Engineering, Product, and UX leadership to pressure-test our priorities: where we can move faster, where we're missing data, and where there's whitespace to innovate. Part of this includes learning and growing with the Engineering team you will collaborate closely with.

• Define what success looks like across our agent portfolio and make sure we're tracking against it , not just shipping, but learning.

• Bring a sharp eye to the competitive landscape, helping us understand what it takes to keep GitLab CI best-in-class in an increasingly agentic world.

Examples of Agentic CI work we have planned for the upcoming year:

• AI Pipeline Builder, the foundational CI agent that auto-creates pipelines for new projects and serves as the launchpad for onboarding new CI users.

• Automate the Fix a Failing Pipeline flow at scale – from dogfooding on internal GitLab projects through to safe, controlled rollout for customers, solving real infrastructure and scalability challenges.

• Build the instrumentation and observability layer that makes agentic CI trustworthy , trigger volume dashboards, retry rates, cost safeguards , so we can measure what's working, catch what isn't, and iterate with confidence.

• Harden the CI pipeline execution infrastructure that these agents depend on: database access patterns, background processing, and job orchestration built to handle the additional load that AI-driven automation introduces at enterprise scale.

You'll shape and scale GitLab CI backend infrastructure to improve performance, reliability, and usability for users running jobs at high volume. You'll design and implement AI-powered features for Agentic CI, including agents, agentic flows, and LLM-backed tooling that integrates with GitLab's Duo Agent Platform. You'll define what success looks like for AI in CI before you build, including baselines, measurable outcomes, and clear signals that help the team learn and iterate. You'll build the instrumentation and observability needed to make AI-assisted CI trustworthy in production, including feature behavior metrics, dashboards, and safeguards. You'll own and drive measurable performance improvements across CI systems (for example, database access patterns, background processing, and job orchestration) by forming hypotheses, running experiments, and validating results with data. You'll write secure, well-tested, maintainable Ruby on Rails code in a large monolith, improving existing features while reducing technical debt and operational risk. You'll lead cross-functional technical work with Product, UX, and Infrastructure, influencing architecture and execution across the Verify stage. You'll share standards, patterns, and learnings with other engineers, raising the bar for responsible AI integration and evidence-driven engineering across CI.

This role requires advanced proficiency with Ruby and Ruby on Rails, with experience building and maintaining reliable backend services in a large codebase. You should have strong PostgreSQL skills, including data modeling, query tuning, and scaling large tables through proactive performance investigation and remediation. You should have hands-on experience building, running, and debugging high-traffic production systems, ideally in CI, workflow orchestration, or adjacent infrastructure-heavy domains. You should have practical experience designing and shipping AI-powered backend features and integrations, including sound judgment about large language model limitations and responsible use in production. You should have a data-driven approach to engineering: defining hypotheses, establishing baseline metrics, instrumenting changes, and measuring outcomes against clear success criteria. You should have familiarity with observability patterns and tools (metrics, logging, tracing) to diagnose issues, improve reliability, and guide iteration. You should have strong backend architecture and delivery practices, including secure design, well-tested code, and strategies for safe rollouts and zero-downtime changes. You should have clear written and verbal communication skills, including writing technical proposals and documentation, and collaborating effectively in a remote, asynchronous, cross-functional environment.

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At Cloudflare, we are on a mission to help build a better Internet. We protect and accelerate any Internet application online without adding hardware, installing software, or changing a line of code. Our network is used by millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.

Role Summary

The Egress team was formed to own a very important aspect of Cloudflare's network-as-a-service: Egress connectivity for our vast portfolio of products. As a member of the Egress team, you will be a key technical contributor to a cutting-edge network software infrastructure used by a growing number of Cloudflare products to connect to any destination from Cloudflare's network.

Responsibilities

• Make daily progress on assigned engineering tasks, such as designing systems, writing specs, writing and pushing code via git, writing release plans for complex changes, rolling out production releases and working with other teams to coordinate system actions
• Participate in daily and ad-hoc team meetings to share progress and collaborate
• Participate in the team’s on-call schedule to ensure uptime of our production systems
• Investigating customer issues that are escalated to the Egress team for triage and resolution
• Responding to questions from other teams in the Egress team’s internal, public chat room
• Using AI-powered tools and systems as part of your daily workflow to analyze and extend codebases, introspect production systems and datasets, and accelerate problem-solving

Requirements

• Programming experience in Go or Rust and a desire to improve your skills in both
• A solid grasp of networking protocols in Layers 3 and 4 of the OSI Model
• Knowledge of HTTP, TLS, and CDN networks
• Experience in implementing secure and highly-available distributed systems
• Strong ability to debug issues in complex systems
• Strong collaboration and communication skills
• Experience/interest in HTTP networking and VPN technologies
• Experience/interest in network performance monitoring and tuning
• Willingness to adopt and integrate AI tools and systems into your engineering workflow

What Makes Cloudflare Special?

We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.

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You will work across the full infrastructure stack, from cloud platforms and networking to application-level performance, and will bridge the gap between high-level research needs and low-level hardware constraints to build the most efficient AI infrastructure in the world. You will help with building the telemetry, cost attribution, and optimization frameworks that ensure every dollar of our infrastructure investment delivers maximum value.

Responsibilities:

• Build and evolve telemetry and monitoring systems to provide deep visibility into infrastructure performance, utilization, and costs across our cloud and datacenter fleets.

• Design and implement cost attribution frameworks for our multi-tenant infrastructure, enabling teams to understand and optimize their resource consumption.

• Identify and resolve performance bottlenecks and capacity hotspots through deep analysis of distributed systems at scale.

• Partner closely with cloud service providers and internal stakeholders to optimize cluster configurations, workload placement, and resource utilization across AI training and inference workloads,including large-scale clusters spanning thousands to hundreds of thousands of machines.

• Develop and champion engineering practices around efficiency, driving a culture of performance awareness and cost-conscious design across Anthropic.

• Collaborate with research and product teams to deeply understand their infrastructure needs, and design solutions that balance performance with cost efficiency.

• Drive architectural improvements and code-level optimizations across multiple services and platforms to deliver measurable utilization and performance gains.

You may be a good fit if you:

• Have 6+ years of relevant industry experience, 1+ year leading large scale, complex projects or teams as a software engineer or tech lead

• Deep expertise in distributed systems at scale, with a strong focus on infrastructure reliability, scalability, and continuous improvement.

• Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java)

• Hands-on experience with cloud infrastructure, including Kubernetes, Infrastructure as Code, and major cloud providers such as AWS or GCP.

• Experience optimizing end-to-end performance of distributed systems, including workload right-sizing and resource utilization tuning.

• You possess a deep curiosity for how things work under the hood and have a proven ability to work independently to solve opaque performance issues

• Experience designing or working with performance and utilization monitoring tools in large-scale, distributed environments.

• Strong problem-solving skills with the ability to work independently and navigate ambiguity.

• Excellent communication and collaboration skills,you will work closely with internal and external stakeholders to build consensus and drive projects forward.

Strong candidates may have:

• Experience with machine learning infrastructure workloads as well as associated networking technologies like NCCL.

• Low level systems experience, for example linux kernel tuning and eBPF

• Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems

• Published work in performance optimization and scaling distributed systems

The annual compensation range for this role is $320,000-$405,000 USD.

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We are seeking a highly skilled and experienced Staff Software Engineer to join our Communication Products team. As a Staff Engineer, you will be responsible for leading the technical vision for ML-powered messaging features, architecting and delivering intelligent capabilities end-to-end, and partnering deeply with ML and product teams.

The Difference You Will Make:

As a Staff Engineer on the team, you will define and drive the technical strategy for integrating ML capabilities into Airbnb's messaging products, including smart replies, message classification, content moderation, translation, and conversational assistance. You will also own the full lifecycle of ML-powered features: from prototyping and experimentation through launch, monitoring, and iteration.

A Typical Day:

• Design, build, and operate the systems that serve ML models within the messaging stack, with a focus on latency, reliability, and scalability
• Write and review technical designs that solve large, open-ended problems at the intersection of ML and product engineering without clearly-known solutions
• Partner with ML, data science, and product teams to identify high-value opportunities, establish evaluation criteria, and close the gap between offline model performance and production impact
• Collaborate with other engineers and cross-functional partners across Messaging, Trust & Safety, Localization, and Platform organizations to align on long-term technical solutions
• Mentor, guide, advocate, and support the career growth of individual contributors
• Establish engineering standards for ML integration across the messaging surface, including feature flagging, A/B testing, observability, and graceful degradation

Your Expertise:

• 9+ years of relevant engineering hands-on work experience
• Bachelors, Masters, or PhD in CS or related field
• Demonstrated experience building and shipping ML-powered product features in production environments, including model serving, feature pipelines, online/offline evaluation, and monitoring
• Exceptional architecture abilities and experience with architectural patterns of large, high-scale applications
• Familiarity with NLP/NLU techniques and large language models, particularly as applied to messaging, conversational AI, or content understanding
• Shipped several large-scale projects with multiple dependencies across teams, specifically at the intersection of ML infrastructure and product engineering
• Technical leadership and strong communication skills with the ability to translate between ML research, product goals, and engineering execution
• Experience operating distributed, real-time systems at scale with high reliability requirements
• Experience with real-time messaging systems or event-driven architectures
• Familiarity with ML infrastructure at scale (e.g., feature stores, model registries, online inference platforms)
• Prior work on trust & safety, content moderation, or internationalization in a messaging context
• Experience with LLM-based product features, including prompt engineering, retrieval-augmented generation, or fine-tuning

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range: $204,000-$255,000 USD

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You will work closely with different business lines across Anduril to help discover and scope new research problems. To be successful in this role, you will need a strong background in machine learning, experience developing and benchmarking ML algorithms, and strong Python skills with experience in ML frameworks such as PyTorch.

The salary range for this role is $220,000-$292,000 USD, and highly competitive equity grants are included in the majority of full-time offers. Additionally, Anduril offers top-tier benefits for full-time employees, including comprehensive medical, dental, and vision plans, income protection, generous time off, family planning and parenting support, mental health resources, professional development, commuter benefits, and relocation assistance.

If you're interested in this opportunity, please reach out to the recruiter assigned to this role to learn more about the specific compensation and benefit details associated with this role.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.

About the Role

Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users , demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. The Systems engineering team owns compute uptime and resilience at massive scale, building the clusters, automation, and observability that make frontier AI research possible and safely deployable to customers.

Responsibilities

• Lead infrastructure projects from design through delivery, owning scope, execution, and outcomes
• Build and maintain systems that support AI clusters at massive scale (thousands to hundreds of thousands of machines)
• Partner with cloud providers and internal teams to solve compute, networking, and reliability challenges
• Tackle difficult technical problems in your domain and proactively fill gaps in tooling, documentation, and processes
• Contribute to operational practices including incident response, postmortems, and on-call rotations

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Lovely office space in which to collaborate with colleagues

Requirements

• 6+ years of software engineering experience
• Have led technical projects end-to-end over multiple months, including scoping, breaking down work, and driving delivery
• Have deep knowledge of distributed systems, reliability, and cloud platforms (Kubernetes, IaC, AWS/GCP)
• Are strong in at least one systems language (Python, Rust, Go, Java)
• Solve hard problems independently and know when to pull others in
• Help teammates grow through knowledge sharing and thoughtful technical guidance
• Communicate clearly in design docs, presentations, and cross-functional discussions

Preferred Qualifications

• Security and privacy best practice expertise
• Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
• Low level systems experience, for example linux kernel tuning and eBPF

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The Network Services team builds and operates the foundational networking that powers CoreWeave's Kubernetes platforms at cloud scale. The team is responsible for container networking, connectivity, and network services that support large-scale, GPU-driven workloads across regions and environments. They focus on scalability, reliability, security, and performance while delivering intuitive platforms for internal teams and customers.

About the Role

As a Senior Engineer focused on our Cilium-based CNI, you will design, build, and operate the container networking layer that underpins CoreWeave's Kubernetes platforms. Day to day, you will work on evolving our CNI stack to support large, high-density GPU clusters with demanding throughput and latency requirements. You will partner closely with Kubernetes, Infrastructure, and Network Services engineers to ensure the platform is highly available, observable, and secure. This role spans architecture, implementation, and operations, with ownership from prototype through production. You will also help shape how our networking platform scales for future growth.

Who You Are

• 5+ years of experience as a Software Engineer or Systems Engineer working on cloud infrastructure or large-scale distributed systems.
• Hands-on production experience with Cilium CNI (or equivalent advanced CNIs), including cluster configuration and lifecycle management.
• Strong understanding of Cilium's eBPF datapath, policy model, and load-balancing mechanisms.
• Deep knowledge of cloud networking concepts, including VPCs, subnets, routing, security groups/ACLs, NAT, and ingress/egress architectures.
• Experience designing multi-tenant network architectures with strong isolation and security.
• Solid grounding in TCP/IP, dynamic routing (e.g., BGP), ECMP, MTU/fragmentation, and overlay/underlay networking (VXLAN, Geneve, encapsulation).
• Experience with network observability and troubleshooting across L3–L7.
• Proficiency in at least one systems language such as Golang or C/C++.
• Experience working in modern CI/CD environments.
• Experience operating Kubernetes at scale, including cluster lifecycle management and debugging networking issues across pods, nodes, and external services.
• Demonstrated ownership of complex systems end-to-end.

Preferred

• Experience operating cloud-scale network services across tens of thousands of nodes and multiple regions.
• Contributions to Cilium, Kubernetes, or related open-source networking projects.
• Experience with eBPF development and performance tuning.
• Experience building Kubernetes operators or controllers.
• Familiarity with service meshes, multi-cluster networking, or cluster mesh solutions.
• Experience in GPU-heavy, HPC, or other performance-sensitive environments.

Wondering if you’re a good fit?

We believe in investing in our people and value candidates who bring diverse experiences , even if you’re not a 100% match on paper. If some of this sounds like you, we’d love to talk.

• You love solving complex distributed systems and networking challenges at scale.
• You’re curious about cloud-native networking, eBPF, and Kubernetes internals.
• You’re an expert in building reliable, scalable infrastructure that runs in production.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

• Medical, dental, and vision insurance
• 100% paid for by CoreWeave
• Company-paid Life Insurance
• Voluntary supplemental life insurance
• Short and long-term disability insurance
• Flexible Spending Account
• Health Savings Account
• Tuition Reimbursement
• Ability to Participate in Employee Stock Purchase Program (ESPP)
• Mental Wellness Benefits through Spring Health
• Family-Forming support provided by Carrot
• Paid Parental Leave
• Flexible, full-service childcare support with Kinside
• 401(k) with a generous employer match
• Flexible PTO
• Catered lunch each day in our office and data center locations
• A casual work environment
• A work culture focused on innovative disruption

Our Workplace

While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.

California Consumer Privacy Act - California applicants only

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.

Export Control Compliance

This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

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Key responsibilities include:

• Designing, commissioning, and upgrading control systems for Solid Rocket Motor production equipment
• Architecting, writing, and debugging Siemens PLC code
• Integrating internal and external FactoryOS software into automation equipment and production lines
• Leading root cause analysis and corrective actions for automation failures
• Installing, configuring, and tuning servo drives/VFDs

Required qualifications include:

• Bachelor's degree in Robotics, Computer Science, Mechanical Engineering, or Electrical Engineering
• 8+ years of experience in controls and automation in a production environment
• Strong skills in Siemens PLC programming (Ladder and Structured Text)
• Proficiency in servo drive and VFD configuration, PID tuning, STO/SS, etc.
• Strong knowledge of ethernet-based communication protocols (ProfiNET, ProfiSAFE, Ethernet IP.)
• Proficiency with electrical component selection and a solid foundation of wire sizing, circuit protection, and heat management in control cabinets
• Experience integrating with SCADA and OT Networking

Preferred qualifications include:

• 10+ years of experience in controls and automation in a production environment
• Experience working in an energetics facility
• Experience with control panel layout, electrical component selection, and cable routing
• Electrical troubleshooting up to 600VAC
• TUV FS Engineer certification (Functional Safety of Machinery)

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Key responsibilities include:

• Design and building of tooling and automated processes for provisioning and execution of Elasticsearch performance benchmarking jobs at scale.
• Defining methodologies and guidelines for performance benchmarking servicing development teams and solution architects.
• Play a lead role in cross-functional team efforts and engagements.
• Mentoring and advising team members on proposed technical solutions.
• Developing reporting for and interpreting of benchmarking results.
• Investigate and assist in resolving performance escalations and capacity planning issues.
• Address and devise solutions for benchmarking disparate use cases and workloads.

Requirements include:

• Software development experience with Python and Linux shell required (Expert Level).
• Familiarity with Linux system-level performance measurement and associated tooling.
• Prior experience in the troubleshooting and root cause analysis of performance issues in complex distributed architectures.
• Prior experience with CI/CD pipelines and automating process workflows.
• Experience in cloud architectures, service models, and operating across multiple cloud service providers, assessing tradeoffs from both performance and deployment perspectives.
• Ability to multitask, effectively manage your time, and collaborate with team members globally across time zones.
• Familiarity with measuring performance and sizing in Linux VM and container environments.
• Experience with performance tuning of Java applications and JVMs.

Bonus points for prior experience with large, distributed search engines and in developing and tuning queries, familiarity with the Elasticsearch Query API and building Kibana dashboards, cloud orchestration with Kubernetes, and experience applying the use of Artificial Intelligence (AI) for devising and expanding benchmarking practices and enhancing benchmarking tooling.

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Your role will be to build champions and enable technical teams alongside our Benelux sales organisation to drive pipeline and close deals. As the technical advocate inside Cloudflare, you will work closely with teams across Sales, Product, Engineering, Customer Support and our channel partners to ensure our customers succeed with Cloudflare security, reliability, and performance solutions.

We are looking for someone with strong experience in pre-sales, partner and account management, and excellent verbal and written communication skills in Dutch and English, suited for both technical and executive-level engagement. You should be comfortable speaking about the Cloudflare vision with all audiences.

Specifically, we are looking for you to:

• Build and maintain long-term technical relationships with prospects, customers and ecosystem organisations across Benelux through demonstrating value, enablement, and uncovering new areas of potential revenue
• Drive technical solution design conversations through use case qualification and collaborative technical wins through demonstrations and proofs-of-concept
• Develop passionate technical champions within the technology ranks of your accounts, helping them drive sales for identified opportunities and build revenue pipeline
• Evangelize and represent Cloudflare through technical thought leadership and expertise
• Be the voice of the market internally at Cloudflare, engaging with and influencing Product and Engineering teams to meet the needs of your accounts and their customers

You will travel requirement in the Benelux to support engagements, attend conferences and industry events, and collaborate with Cloudflare teammates.

Examples of desirable skills, knowledge and experience include:

• Fluency in Dutch and English (verbal and written)
• Ability to communicate complex technical concepts to both technical and non-technical audiences, including C-level stakeholders
• Strong presentation and storytelling skills (whiteboarding, demos, executive briefings)
• Experience managing technical sales cycles end-to-end
• Ability to articulate business value and ROI of technical solutions, not just features
• Experience working within an integrated account team (alongside Account Executives, Customer Success, BDRs, and channel partners)
• Networking technologies including TCP/IP, UDP, DNS (authoritative and recursive, DNSSEC), IPv4/IPv6, BGP routing, Autonomous Systems, subnetting
• Tunneling and connectivity: GRE, IPsec, MPLS, SDWAN
• Cloud networking concepts: VPCs, peering, interconnect
• DDoS attack types (L3/L4/L7) and mitigation strategies
• Web Application Firewall (WAF) rule configuration and tuning
• VPN concepts and their limitations relative to Zero Trust approaches
• API security: API Gateway, rate limiting, schema validation, abuse prevention
• Bot management concepts and detection techniques
• SASE concepts and Zero Trust Networking architectures (ZTNA, CASB, SWG, DLP, RBI as integrated platform)
• Zero Trust Network Access (ZTNA) vs. traditional VPN architecture
• HTTP technologies and reverse proxy architecture: WAF, CDN, caching mechanics
• Detailed understanding of the flow from user to application, including hybrid cloud architectures
• Working knowledge of major cloud platforms: AWS, Azure, GCP (architecture patterns, native security tooling, VPC/peering models)
• Familiarity with Infrastructure-as-Code concepts (e.g. Terraform)
• Cloudflare Workers and the edge compute model (JavaScript/TypeScript)
• Familiarity with related primitives: KV, Object storage, serverless compute
• Familiarity with the competitive landscape across Cloudflare's product areas
• Understanding of why customers move from on-premises appliances to cloud-delivered security
• Awareness of relevant industry verticals: Financial Services, eCommerce, Gaming, Media, SaaS, Healthcare

We value intellectual curiosity, adaptability, and a collaborative spirit. On the Solutions Engineering team, you will find an environment where everyone brings different strengths and jumps in to help each other. If you are passionate about technology and look forward to helping customers and ecosystem organisations realise the full promise of Cloudflare, we'd love to hear from you.

What makes Cloudflare special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend

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Our team is responsible for building systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. You will work on high-impact systems that improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems.

As a Senior Machine Learning Engineer, you will:

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with strong reliability, observability, and automated retraining
• Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems
• Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
• Improve system performance across latency, throughput, and model quality metrics
• Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment

Basic Qualifications:

• 3-5+ years of experience building, deploying, and operating machine learning systems in production
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
• Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
• Experience improving measurable metrics through applied machine learning

Preferred Qualifications:

• Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems
• Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• Experience working with real-time systems and low-latency production environments
• Background in feature engineering, model optimization, and production monitoring
• Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
• Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams:

• Ads Measurement Modeling
• Ads Targeting and Retrieval
• Advertiser Optimization
• Ads Marketplace Quality
• Ads Creative Effectiveness
• Ads Foundational Representations
• Ads Content Understanding
• Ads Ranking
• Feed Relevance
• Search and Answers Relevance
• ML Understanding
• Notifications Relevance

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

Pay Transparency:

This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/. To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is $216,700-$303,400 USD

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From statistical models all the way down to deep and foundational models, feature augmentation and auto-tuning, our Applied ML/AI team works on some of the most complex, most interesting problems facing businesses, making Databricks' infrastructure and products as performant and cost-efficient as possible.

This is a high-impact problem as our customers look at us to deliver the most out of their data.

Key responsibilities include:

• Building features and running end-to-end systems in a small team of experienced engineers and data scientists.
• Shaping the direction of our applied ML investment by engaging with engineering and product teams across the company.
• Driving the development and deployment of state-of-the-art ML/AI models and systems that directly impact the capabilities and performance of Databricks’ products, infrastructure, and services.
• Architecting and implementing robust, scalable ML infrastructure, including model training and serving components to support seamless integration of AI/ML models into production environments.
• Working on novel modeling techniques in the field of ML for forecasting.

What we look for:

• 2-8 years of machine learning engineering experience in high-velocity, high-growth companies.
• Strong understanding of both computer systems and statistics.
• Experience developing AI/ML systems at scale in production.
• Strong track record of ML modeling that goes beyond using standard libraries.
• Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews, and deployment.
• A large breadth of knowledge or willingness to develop mathematical modelling beyond the ML.

Why Join Us?

At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.

If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you!

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At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.

We protect and accelerate any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks.

Role Summary

The Egress team was formed to own a very important aspect of Cloudflare's network-as-a-service: egress connectivity for our vast portfolio of products. As a member of the Egress team, you will be a key technical contributor to a cutting edge network software infrastructure used by a growing number of Cloudflare products to connect to any destination from Cloudflare's network.

Among the products powered by this technology is WARP, our Zero Trust platform, and Cloudflare's egress proxy for the iCloud Private Relay product. You will work closely with various Engineering teams to translate their requirements into new capabilities on the platform. Likewise you will partner with Network Engineering and SRE to ensure that the technology makes the best use of Cloudflare's world-class edge network.

Responsibilities

• Make daily progress on assigned engineering tasks, such as designing systems, writing specs, writing and pushing code via git, writing release plans for complex changes, rolling out production releases and working with other teams to coordinate system actions

• Participate in daily and ad-hoc team meetings to share progress and collaborate

• Participate in the team’s on-call schedule to ensure uptime of our production systems

• Investigating customer issues that are escalated to the Egress team for triage and resolution

• Responding to questions from other teams in the Egress team’s internal, public chat room

• Using AI-powered tools and systems as part of your daily workflow to analyze and extend codebases, introspect production systems and datasets, and accelerate problem-solving

Requirements

• Programming experience in Go or Rust and a desire to improve your skills in both

• A solid grasp of networking protocols in Layers 3 and 4 of the OSI Model

• Knowledge of HTTP, TLS, and CDN networks

• Experience in implementing secure and highly-available distributed systems

• Strong ability to debug issues in complex systems

• Strong collaboration and communication skills

• Experience/interest in HTTP networking and VPN technologies

• Experience/interest in network performance monitoring and tuning

• Willingness to adopt and integrate AI tools and systems into your engineering workflow

What Makes Cloudflare Special?

We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.

Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.

Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.

1.1.1.1: We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released.

Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers.

Sound like something you’d like to be a part of? We’d love to hear from you!

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The Environment Scaling team is a team of researchers and engineers whose goal is to improve the intelligence of our public models for novel verticals and use cases. The team builds the training environments that fuel RL at scale. This is a unique role that combines executing directly on ML research, data operations, and project management to improve our models.

Responsibilities:

• Improve and execute our fine-tuning strategies for adapting Claude to new domains and tasks
• Manage technical relationships with external data vendors, including evaluation of data quality and reward design
• Collaborate with domain experts to design data pipelines and evaluations
• Explore novel ways of creating RL environments for high value tasks
• Develop and improve QA frameworks to catch reward hacking and ensure environment quality
• Partner with other RL research teams and product teams to translate capability goals into training environments and evals

You may be a good fit if you:

• Have experience with fine-tuning large language models for specific domains or real-world use cases and/or domain expertise in an area where we would like to make our models more useful.
• Have experience with reinforcement learning, reward design, or training data curation for LLMs
• Are comfortable managing technical vendor relationships and iterating quickly on feedback
• Find value in reading through datasets to understand them and spot issues
• Have strong project management and interpersonal skills
• Are passionate about making AI more useful and accessible across different industries
• Are excited about a role that includes a combination of ML research, data operations, and project management

Strong candidates may also:

• Have experience training production ML systems
• Be familiar with distributed systems and cloud infrastructure
• Have domain expertise in an area where we would like to make our models more useful
• Have experience working with external vendors or technical partners

The annual compensation range for this role is $350,000-$850,000 USD.

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You'll architect and implement infrastructure that powers our GraphQL-based federated query system for seamless data access across platforms including BigTable, BigQuery, and Solr+.

This is a unique opportunity to influence the technical direction of ZoomInfo's core data infrastructure, addressing complex challenges such as data freshness, multi-tenant isolation, and real-time data processing at scale.

Responsibilities:

• Design and build scalable infrastructure for GTM Store and ZDP with sub-second query latency.
• Architect and implement metadata-driven GraphQL APIs for dynamic schema generation and query federation.
• Develop asynchronous secondary indexing systems for scaling capacity and reducing primary data store load.
• Design real-time analytics streaming data pipelines from BigTable to BigQuery.
• Develop data mutation and deletion frameworks supporting GDPR compliance and schema evolution.
• Implement CDC pipelines and calculated field processing for derived data views.
• Build observability and monitoring solutions for real-time issue diagnosis across distributed data systems.
• Create batch and streaming data processing workflows for complex relationships at scale.
• Collaborate with engineering leaders and product managers to define the technical roadmap.
• Mentor engineers and establish best practices for cloud-native data infrastructure development.
• Partner with cross-functional teams to address data platform requirements and challenges.
• Drive solutions for data freshness, query performance, and system reliability challenges.

Qualifications:

• Bachelor's degree in Computer Science, Software Engineering, or related field (or equivalent experience).
• 10+ years of software engineering experience building large-scale data platforms.
• Expertise with distributed NoSQL databases and data warehousing systems.
• Strong experience with Java 8+, Scala, Kotlin, GoLang for data systems development.
• Proven experience with GCP or AWS and cloud-native architectures.
• Experience with streaming/real-time data processing technologies.
• Strong system design skills for architecting multi-tenant, distributed systems.
• Hands-on experience with Google Cloud Platform services.
• Knowledge of CDC patterns, event sourcing, and streaming architectures.
• Experience solving data freshness and consistency challenges in distributed systems.
• Background in building observability and monitoring solutions for data platforms.
• Familiarity with metadata management and schema evolution.
• Experience with Kubernetes for deploying data services.
• SQL query optimization and performance tuning expertise.
• Experience building GraphQL APIs with federated or metadata-driven schema generation.
• Strong problem-solving skills and the ability to debug complex distributed systems issues.
• Excellent communication skills for explaining technical decisions to diverse audiences.
• Self-directed with the ability to drive initiatives independently while collaborating with teams.
• Passion for building reliable, observable, and maintainable systems.
• Experience promoting diverse, inclusive work environments.

Actual compensation offered will be based on factors such as the candidate’s work location, qualifications, skills, experience and/or training. Your recruiter can share more information about the specific salary range for your desired work location during the hiring process.

We want our employees and their families to thrive. In addition to comprehensive benefits we offer holistic mind, body and lifestyle programs designed for overall well-being. Learn more about ZoomInfo benefits here.

Below is the US base salary for this position. Additional compensation such as Bonus, Commission, Equity and other benefits may also apply.

$163,800-$257,400 USD

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You'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.

Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

We conduct all interviews in Python, and this role may require responding to incidents on short-notice, including on weekends.

Responsibilities:

Implement and optimize post-training techniques at scale on frontier models

Conduct research to develop and optimize post-training recipes that directly improve production model quality

Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation

Develop tools to measure and improve model performance across various dimensions

Collaborate with research teams to translate emerging techniques into production-ready implementations

Debug complex issues in training pipelines and model behavior

Help establish best practices for reliable, reproducible model post-training

You may be a good fit if you:

Thrive in controlled chaos and are energized, rather than overwhelmed, when juggling multiple urgent priorities

Adapt quickly to changing priorities

Maintain clarity when debugging complex, time-sensitive issues

Have strong software engineering skills with experience building complex ML systems

Are comfortable working with large-scale distributed systems and high-performance computing

Have experience with training, fine-tuning, or evaluating large language models

Can balance research exploration with engineering rigor and operational reliability

Are adept at analyzing and debugging model training processes

Enjoy collaborating across research and engineering disciplines

Can navigate ambiguity and make progress in fast-moving research environments

Strong candidates may also:

Have experience with LLMs

Have a keen interest in AI safety and responsible deployment

We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems.

However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role.

The annual compensation range for this role is $350,000-$500,000 USD.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.

About the role

Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.

You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.

Responsibilities

• Implement and optimize post-training techniques at scale on frontier models
• Conduct research to develop and optimize post-training recipes that directly improve production model quality
• Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
• Develop tools to measure and improve model performance across various dimensions
• Collaborate with research teams to translate emerging techniques into production-ready implementations
• Debug complex issues in training pipelines and model behavior
• Help establish best practices for reliable, reproducible model post-training

You may be a good fit if you:

• Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities
• Adapt quickly to changing priorities
• Maintain clarity when debugging complex, time-sensitive issues
• Have strong software engineering skills with experience building complex ML systems
• Are comfortable working with large-scale distributed systems and high-performance computing
• Have experience with training, fine-tuning, or evaluating large language models
• Can balance research exploration with engineering rigor and operational reliability
• Are adept at analyzing and debugging model training processes
• Enjoy collaborating across research and engineering disciplines
• Can navigate ambiguity and make progress in fast-moving research environments

Strong candidates may also:

• Have experience with LLMs
• Have a keen interest in AI safety and responsible deployment

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links,visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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You want to build the cutting-edge systems that train AI models like Claude. You're excited to work at the frontier of machine learning, implementing and improving advanced techniques to create ever more capable, reliable and steerable AI.

As an ML Systems Engineer on our Reinforcement Learning Engineering team, you'll be responsible for the critical algorithms and infrastructure that our researchers depend on to train models. Your work will directly enable breakthroughs in AI capabilities and safety.

You'll focus obsessively on improving the performance, robustness, and usability of these systems so our research can progress as quickly as possible.

Our finetuning researchers train our production Claude models, and internal research models, using RLHF and other related methods. Your job will be to build, maintain, and improve the algorithms and systems that these researchers use to train models.

You'll be responsible for improving the speed, reliability, and ease-of-use of these systems.

Strong candidates may also have experience with:

High performance, large scale distributed systems Large scale LLM training Python Implementing LLM finetuning algorithms, such as RLHF

Representative projects:

Profiling our reinforcement learning pipeline to find opportunities for improvement Building a system that regularly launches training jobs in a test environment so that we can quickly detect problems in the training pipeline Making changes to our finetuning systems so they work on new model architectures Building instrumentation to detect and eliminate Python GIL contention in our training code Diagnosing why training runs have started slowing down after some number of steps, and fixing it Implementing a stable, fast version of a new training algorithm proposed by a researcher

Deadline to apply: None. Applications will be reviewed on a rolling basis.

The annual compensation range for this role is $500,000-$850,000 USD.

Logistics:

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.

Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links,visit anthropic.com/careers directly for confirmed position openings.

How we're different:

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles.

We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time.

As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process

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Strong customer advocacy, relationship building, and communications skills are essential for this role. You will need to be able to easily pivot from delivery to strategic engagements with customers. You will work with the wider Elastic organisation to support the customer's goals, their strategic requirements, and their journey with Elastic.

Responsibilities:

• Strong customer advocacy, relationship building, and communications skills
• Ability to easily pivot from delivery to strategic engagements with customers
• Work with the wider Elastic organisation to support the customer's goals, their strategic requirements, and their journey with Elastic
• Ownership of the strategic roadmap with the customer including quarterly strategic sessions with senior and key stakeholders
• Solution design, development, and integration of Elastic products and APIs, platform architecture, and capacity planning in mission-critical environments
• Comfortable working remotely in a highly distributed team
• Development of demos and proof-of-concepts that highlight the value of the Elastic Stack
• Data modelling, query development and optimisation, cluster tuning and scaling with a focus on fast search and analytics at scale
• Solving our customers' most challenging data problems
• Working closely with the Elastic engineering, product management, and support teams to identify feature enhancements, extensions
• Engaging with the Elastic Sales team to scope opportunities while assessing technical risks, questions, or concerns

Requirements:

• Hands-on experience and an understanding of Elasticsearch and/or Lucene
• Minimum of 2 years' experience as a Software Engineer, System Administrator, or DevOps Engineer
• Minimum of 5 years' experience working as a Consultant, working to deliver and execute on professional services engagements
• Currently holding current UK security clearance, or has previously held security clearance, or is willing to undergo security clearance
• Experience as a technical instructor or public speaker to large audiences on enterprise infrastructure software technology to engineers, developers, and other technical positions
• Excel at working directly with customers to gather, prioritise, plan and execute solutions to customer business requirements as it relates to our technologies
• Understanding and passion for open-source technology and knowledge and proficient in at least one programming language
• Hands-on experience with large distributed systems from an architecture and development perspective
• Knowledge of information retrieval and/or analytics domain
• The nature of the work that you will be doing will require a high percentage of work onsite with customers, and you should be expected to travel as a result of this requirement
• Understanding of Linux, Java, and databases

Bonus Points:

• Deep understanding of Elasticsearch and Lucene, including Elastic Certified Engineer certification
• BS, MS, or PhD in Computer Science or related engineering discipline
• Strong knowledge of Java and Linux/Unix environment, software development, and/or experience with distributed systems
• Experience and interest in delivering and/or developing product training
• Experience contributing to an open-source project or documentation

As a distributed company, diversity drives our identity. Whether you're looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn't matter if you're just out of college or your children are; we need you for what you can do. We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do.

Competitive pay based on the work you do here and not your previous salary Health coverage for you and your family in many locations Ability to craft your calendar with flexible locations and schedules for many roles Generous number of vacation days each year Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service Up to 40 hours each year to use toward volunteer projects you love Embracing parenthood with minimum of 16 weeks of parental leave

Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation.

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You will have the opportunity to contribute directly to research projects yourself and have a direct impact on our ability to scale reward development across domains. You will work closely with researchers and translate ambiguous requirements into well-scoped engineering projects.

To be successful in this role, you should have prior research experience and be excited to work closely with researchers. You should have strong Python skills and experience with ML workflows and data pipelines, and building related infrastructure/tooling/platforms. You should be comfortable working across the stack, ranging from data pipelines to experiment tracking to user-facing tooling.

Strong candidates may also have experience with ML research, building internal tooling and platforms for ML researchers, data quality assessment and pipeline optimization, experiment tracking, evaluation frameworks, or MLOps tooling. They may also have experience with large-scale data processing, Kubernetes, distributed systems, or cloud infrastructure, and familiarity with reinforcement learning or fine-tuning workflows.

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As a research engineer, you'll partner with the product org to ensure that the vision improvements you deliver impact Claude's performance on real-world tasks. You'll also work with our product org to find solutions to our most vexing API customer challenges related to vision and spatial reasoning.

Strong candidates may also have experience with large-scale pretraining, SL, and RL on language models, deep learning research on images, video, or other modalities, developing complex agentic systems using LLMs, high-performance ML systems (GPUs, TPUs, JAX, PyTorch), and large-scale ETL and data pipeline development.

The annual compensation range for this role is $350,000-$850,000 USD.

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The Imagine Product team is redefining AI-driven media experiences for Grok users worldwide. You'll build and scale robust, high-performance systems that power immersive, multi-modal media interactions,leveraging cutting-edge AI to enable seamless generation, processing, and delivery of images, video, audio, and beyond.

Your work will drive engaging, real-time user experiences that captivate and delight millions, turning advanced multimodal models into production-grade features. If you're a driven problem-solver passionate about AI, media technologies, and creating scalable solutions that shape the future of consumer AI, this is your opportunity to make a lasting impact.

Responsibilities

• Design and implement scalable systems to support Grok's AI-driven media experiences, ensuring high performance, reliability, and low-latency at global scale.
• Architect robust infrastructure for real-time multi-modal interactions, including handling generation requests, media processing, and seamless integration with frontend and model serving layers.
• Build and optimise large-scale data pipelines to ingest, process, and analyse multi-modal data (images, video, audio), fueling continuous improvement and personalisation of Grok's media capabilities.
• Collaborate closely with frontend engineers, AI researchers, and product teams to deliver captivating, media-rich features and end-to-end user experiences.
• Own full-cycle development of solutions: from system design and prototyping to deployment, monitoring, observability, and iterative refinement.
• Deliver production-ready, maintainable code that powers features reaching hundreds of millions of users.

Basic Qualifications

• Proficiency in Python or Rust, with a strong track record of writing clean, efficient, maintainable, and scalable code.
• Experience designing and building systems for consumer-facing products, with emphasis on performance, reliability, and handling high-throughput workloads.
• Hands-on expertise in large-scale data infrastructure and pipelines, particularly for multi-modal or media-heavy AI applications.
• Proven ability to deliver robust, production-grade solutions to millions of users while maintaining high standards of quality and uptime.
• Strong problem-solving skills and a passion for turning innovative ideas into high-impact, scalable realities.
• Deep enthusiasm for AI and media technologies, with a commitment to building user-focused products that inspire and engage.

Preferred Skills and Experience

• Experience with real-time systems, inference serving, or multi-modal data processing at scale.
• Familiarity with distributed systems, containerisation (e.g., Kubernetes), observability tools, or performance tuning for AI workloads.
• Background in AI-driven consumer products or media generation technologies.
• Track record collaborating across engineering, research, and product teams to ship delightful features quickly.

Compensation and Benefits

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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Our focus is delivering the best possible chat interface,seamless, intuitive, and maximally useful,to turn Grok into an essential "everything app" that amplifies human productivity across any domain.

Help build the portal that lets users accomplish anything: ask questions, create slide decks, solve puzzles, or tackle real work in engineering, law, medicine, and beyond. We're creating an easy-to-use experience that works flawlessly, driving a 10x increase in what knowledge workers can achieve.

No prior AI experience required,just sharp thinking, relentless execution, and passion for AI that redefines what's possible. Own end-to-end features that delight millions, collaborating closely with model and research teams to ship breakthroughs at pace.

Responsibilities:

• Design and deliver polished, scalable user-facing features and APIs for Grok's chat experience.

• Innovate on frameworks for rapid experimentation to iterate quickly and keep Grok leading in reasoning and utility.

• Architect high-performance systems for personalized, reliable interactions at global scale.

• Build and optimize data pipelines using real-time user signals to continuously improve the product.

• Own projects from ideation to deployment and monitoring, gathering feedback to refine the seamless portal vision.

Basic Qualifications:

• Proactive self-starter who turns bold ideas into high-impact realities with focused execution.

• Expert in TypeScript, Python, or Rust, with experience crafting clean, maintainable code.

• Skilled in scalable architectures, Kubernetes, observability, and production tuning for performance/reliability.

• Track record shipping consumer-facing products to millions, emphasizing user delight and feedback.

• Passionate about AI's transformative potential and committed to building indispensable tools users rely on daily.

Compensation and Benefits:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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You'll partner with Product, Engineering, and Policy to shape the behavior and responses of LLM models, utilizing mastery of the art and structure of language to create principles, response strategies, and examples for the content quality of Gemini models. You'll define and establish comprehensive content standards and specifications for Gemini models, addressing factors like factual accuracy, privacy, safety, personality, tone, and style.

Key responsibilities include diagnosing content quality issues, developing strategies and alignment for implementation and hillclimbing across product areas, and creating scalable solutions to UX and process challenges across teams. You'll also advocate for a user-centered approach to model output, ensuring that the content the model generates meets the needs and expectations of our users.

To set you up for success as a Model UX Designer at Google DeepMind, we look for the following skills and experience:

• 5+ years of experience on user-focused writing, including work in hardware, software, digital agencies, creative industries, journalism, or other relevant areas
• Experience in shaping content for multi-disciplinary projects
• A portfolio of content strategies and longer-form writing samples

In addition, the following would be an advantage:

• Experience training and tuning large language models or other generative AI technologies
• Experience being a driver in a fast-paced, startup environment
• Experience working on multi-modal platforms, like voice-driven experiences or AR/VR
• Experience gathering and working with data to identify loss patterns and create actionable insights
• Experience developing AI-driven prototypes

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Key responsibilities include:

• Post-training/instruction tuning state-of-the-art LLMs, focusing on text-to-text, image/video/audio-to-text modalities and agentic capabilities
• Exploring data, reasoning, and algorithmic solutions to ensure Gemini Models are safe, maximally helpful, and work for everyone
• Improve Gemini's adversarial robustness, with a focus on high-stakes abuse risks
• Design and maintain high-quality evaluation protocols to assess model behavior gaps and headroom related to safety and fairness
• Develop and execute experimental plans to address known gaps, or construct entirely new capabilities
• Drive innovation and enhance understanding of Supervised Fine Tuning and Reinforcement Learning fine-tuning at scale

To succeed as a Research Scientist in the Gemini Safety team, we look for the following skills and experience:

• PhD in Computer Science, a related field, or equivalent practical experience
• Significant LLM post-training experience
• Experience in Reward modeling and Reinforcement Learning for LLMs Instruction tuning
• Experience with Long-range Reinforcement learning
• Experience in areas such as Safety, Fairness, and Alignment
• Track record of publications at NeurIPS, ICLR, ICML
• Experience taking research from concept to product
• Experience with collaborating or leading an applied research project
• Strong experimental taste: Good judgment regarding baselines, ablations, and what is worth testing
• Experience with JAX

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This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google and top customers.

You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest-generation models.

We are looking for engineers with a strong track record of building and shipping AI-powered software, ideally with experience in early-stage environments where they have contributed to scaling products from initial concept to production.

The ideal candidate will be motivated by the opportunity to drive product & business impact.

Key responsibilities:

• Harness frontier models to drive real-world high-impact outcomes

• Build evaluations, training data, and infrastructure to support AI deployments and rapid iterations

• Collaborate with researchers and product managers to translate research advancements into tangible product features.

• Contribute to the development of best practices for building and deploying generative AI applications.

• Contribute signal to influence the development of frontier models

• Lead the architecture and development of new products & features from 0 to 1.

About you:

In order to set you up for success as a Staff Research Engineer, Applied AI at Google DeepMind, we look for the following skills and experience:

Required Skills:

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development, and with data structures/algorithms.

• 5 years of hands-on experience in AI research (e.g. RL, finetuning, evals), AI applications, or model deployment

• Proven experience in rapidly developing and shipping software products.

• Deep understanding of software development best practices, including testing & deployment.

• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).

• Substantial experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.

• Ability to work in a fast-paced environment and adapt to changing priorities.

Preferred Skills:

• Experience with generative AI research or applications.

• Contributions to open-source projects.

• Experience working in, or founding early stage startups.

• Experience delivering software solutions in a fast-paced, customer-facing environment.

If you are a passionate machine learning engineer with a drive to build innovative products and a desire to work at the forefront of AI, we encourage you to apply!

The US base salary range for this full-time position is between $197,000 - $291,000 + bonus + equity + benefits.

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This role focuses on automating processes, building and implementing robust observability solutions, and ensuring seamless operations for mission-critical AI infrastructure.

The ideal candidate will combine strong coding abilities with hands-on data center experience to build scalable reliability services, optimize system performance, and minimize downtime,including close partnership with facility operations to address physical infrastructure impacts.

In an era where AI workloads demand near-zero downtime, this position plays a pivotal role in bridging software engineering principles with physical data center realities.

By prioritizing automation and observability, team members in this role can reduce mean time to recovery (MTTR) by up to 50% through proactive monitoring and automated remediation, based on industry benchmarks from high-scale environments like those at hyperscale cloud providers.

Responsibilities:

• Design, develop, and deploy scalable code and services (primarily in Python and Rust, with flexibility for emerging languages) to automate reliability workflows, including monitoring, alerting, incident response, and infrastructure provisioning.

• Implement and maintain observability tools and practices, such as metrics collection, logging, tracing, and dashboards, to provide real-time insights into system health across multiple data centers,open to innovative stacks beyond traditional ones like ELK.

• Collaborate with cross-functional teams,including software development, network engineering, site operations, and facility operations (critical facilities, mechanical/electrical teams, and data center infrastructure management),to identify reliability bottlenecks, automate solutions for fault tolerance, disaster recovery, capacity planning, and physical/environmental risk mitigation (e.g., power redundancy, cooling efficiency, and environmental monitoring integration).

• Troubleshoot and resolve complex issues in data center environments, including hardware failures, environmental anomalies, software bugs, and network-related problems, while adhering to reliability principles like error budgets and SLAs.

• Optimize Linux-based systems for performance, security, and reliability, including kernel tuning, container orchestration (e.g., Kubernetes or emerging alternatives), and scripting for automation.

• Understand network topologies and concepts in large-scale, multi-data center environments to effectively troubleshoot connectivity, routing, redundancy, and performance issues; integrate observability into data center interconnects and facility-level controls for rapid diagnosis and automation.

• Participate in on-call rotations, post-incident reviews (blameless postmortems), and continuous improvement initiatives to enhance overall site reliability, including joint exercises with facility teams for physical failover and recovery scenarios.

• Mentor junior team members and document processes to foster a culture of automation, knowledge sharing, and adaptability to new technologies.

Basic Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a closely related technical field (or equivalent professional experience).

• 5+ years of hands-on experience in site reliability engineering (SRE), infrastructure engineering, DevOps, or systems engineering, preferably supporting large-scale, distributed, or production environments.

• Strong programming skills with proven production experience in Python (required for automation and tooling); experience with Rust or willingness to work in Rust is a plus, but strong coding fundamentals in at least one systems-level language (e.g., Python, Go, C++) are essential.

• Solid experience with Linux systems administration, performance tuning, kernel-level understanding, and scripting/automation in production environments.

• Practical knowledge of containerization and orchestration technologies, such as Docker and Kubernetes (or similar systems).

• Experience implementing observability solutions, including metrics, logging, tracing, monitoring tools (e.g., Prometheus, Grafana, or alternatives), alerting, and dashboards.

• Familiarity with troubleshooting complex issues in distributed systems, including software bugs, hardware failures, network problems, and environmental factors.

• Understanding of networking fundamentals (TCP/IP, routing, redundancy, DNS) in large-scale or multi-site environments.

• Experience participating in on-call rotations, incident response, post-incident reviews (blameless postmortems), and reliability practices such as error budgets or SLAs.

• Ability to collaborate effectively with cross-functional teams (software engineers, network teams, site/facility operations, mechanical/electrical teams).

Preferred Skills and Experience:

• 7+ years of experience in SRE or infrastructure roles, ideally in hyperscale, cloud, or AI/ML training infrastructure environments with multi-data center setups.

• Hands-on experience operating or scaling Kubernetes clusters (or equivalent orchestration) at large scale, including automation for provisioning, lifecycle management, and high-availability.

• Proficiency in Rust for systems programming and performance-critical components.

• Direct experience integrating software reliability tools with physical data center infrastructure.

• Experience with observability tools and practices, such as metrics collection, logging, tracing, and dashboards.

• Familiarity with containerization and orchestration technologies, such as Docker and Kubernetes (or similar systems).

• Experience with Linux systems administration, performance tuning, kernel-level understanding, and scripting/automation in production environments.

• Understanding of networking fundamentals (TCP/IP, routing, redundancy, DNS) in large-scale or multi-site environments.

• Experience participating in on-call rotations, incident response, post-incident reviews (blameless postmortems), and reliability practices such as error budgets or SLAs.

• Ability to collaborate effectively with cross-functional teams (software engineers, network teams, site/facility operations, mechanical/electrical teams).

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This team moves very quickly. Claude writes a lot of the code we commit, which means the bottleneck isn't typing , it's judgment, taste, and the ability to react to what researchers need next. You'll iterate on data collection strategies to distill the knowledge of thousands of human experts around the world into our models, and you'll do it in a loop that closes in hours and days, not quarters or months.

Our work spans teaching models to use computers effectively, advancing code generation through RL, pioneering fundamental RL research for large language models, and building the scalable training methodologies behind our frontier production models. The RL org is organized around four goals: solving the science of long-horizon tasks and continual learning, scaling RL data and environments to be comprehensive and diverse, automating software engineering end-to-end, and training the frontier production model.

Our engineering teams build the environments, evaluation systems, data pipelines, and tooling that make all of this possible , from realistic agentic training environments and scalable code data generation to human data collection platforms and production training operations.

Responsibilities:

• Build and extend web platforms for RL environment creation, management, and quality review , including environment configuration, versioning, and validation workflows
• Develop vendor-facing interfaces and tooling that let external partners create, submit, and iterate on training environments with minimal friction
• Design and implement platforms for human data collection at scale, including labeling workflows, quality assurance systems, and feedback mechanisms that surface reward signal integrity issues early
• Build evaluation dashboards and observability UIs that give researchers real-time insight into environment quality, training run health, and reward hacking
• Create backend services and APIs that connect environment authoring tools, data collection systems, and RL training infrastructure
• Build and expand scalable code data generation pipelines, producing diverse programming tasks with robust reward signals across languages and difficulty levels
• Develop onboarding automation and documentation tooling so new vendors and internal users ramp up in hours, not weeks
• Partner closely with RL researchers, data operations, and vendor management to translate ambiguous requirements into well-scoped, well-designed products

You May Be a Good Fit If You:

• Have strong software engineering fundamentals and real full-stack range , you're comfortable owning a surface from database schema to frontend
• Are proficient in Python and a modern web stack (React, TypeScript, or similar)
• Have a track record of shipping systems that solved a hard problem, not just shipped on time , e.g. you built the thing that made your team 10x faster, or the internal tool nobody thought was possible
• Operate with high agency: you identify what needs to be done and drive it forward without waiting for a ticket
• Have found yourself wondering "why isn't this moving faster?" in previous roles , and then have done something about it
• Care about UX and can build interfaces that are intuitive for both technical researchers and non-technical labelers
• Communicate clearly with researchers, operations teams, and engineers, and can turn vague asks into well-scoped work
• Thrive in a fast-moving environment where priorities shift, Claude is your pair programmer, and the next problem is often one nobody has solved before
• Care about Anthropic's mission to build safe, beneficial AI and want your work to contribute directly to it

Strong Candidates May Also Have:

• Built data collection, labeling, or annotation platforms , ideally ones that had to scale across many vendors or many task types
• Background building multi-tenant platforms with role-based access, audit trails, and vendor management workflows
• Experience with cloud infrastructure (GCP or AWS), Docker, and CI/CD pipelines
• Familiarity with LLM training, fine-tuning, or evaluation workflows
• Experience with async Python (Trio, asyncio) or high-throughput API design
• Background in dashboards, monitoring, or observability tooling
• Experience working directly with external vendors or partners on technical integrations
• A background that isn't a straight line , e.g. math or physics into SWE, competitive programming, research into engineering, or a side project that outgrew its scope

Representative Projects:

• Building a unified platform for human data collection that integrates labeling workflows, vendor management, and QA for complex agentic tasks
• Developing vendor onboarding automation that handles Docker registry access, API token management, and environment validation
• Creating evaluation and observability dashboards that catch reward hacks, measure environment difficulty, and give real-time feedback during production training
• Building environment quality review workflows that let researchers browse, grade, and provide feedback on training environments
• Developing automated environment quality pipelines that validate correctness and difficulty calibration before environments hit production training
• Building internal tools for browsing and analyzing training run results, environment statistics, and data collection progress

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About Us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence.

The Role

In this role, you'll work with a team of elite researchers and engineers to design and implement post-training strategies that enhance Gemini’s capabilities in code security analysis. You will bring contributions to our ML innovation, post-training refinement (SFT/RLHF), advanced evaluation, and data generation to ensure our models can reliably perform safe and powerful code security analysis.

Key responsibilities:

• Design and Implement advanced post-training algorithms (SFT, RLHF, RLAIF) to optimize Gemini for code security tasks and secure coding practices.

• Diagnose and interpret training outcomes (regressions in coding ability, gains in security reasoning), and propose solutions to improve model capabilities.

• Actively monitor and evolve the system's performance through metric design.

• Develop reliable automated evaluation pipelines for code security that are strongly correlated with human security expert judgment.

• Construct complex benchmarks to probe the limits of the model’s ability to reason about control flow, memory safety, and software weakness.

About You

We are seeking individuals who excel in fast-pacing environments and are eager to contribute to the advancement of AI. We highly value the ability to invent novel solutions to complex problems, embracing a can-do and fail-fast mindset. We are looking for someone who genuinely believes in the future of AI and is committed to devoting their energy in this field.

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• BSc, MSc or PhD/DPhil degree in computer science, stats, machine learning or similar experience working in industry

• Deep understanding of statistics is strongly preferred

• Experiences in fine-tuning and adaptation of LLMs (e.g. advanced prompting, supervised fine-tuning, RLHF)

• Strong knowledge of systems design and data structures

• Proven experience with TensorFlow, JAX, PyTorch, or similar leading deep learning frameworks

• Recent experience conducting applied research to improve the quality and training/serving efficiency of large transformer-based models

• A passion for Artificial Intelligence.

• Excellent communication skills and proven interpersonal skills, with a track record of effective collaboration with cross-functional teams

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We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.

As a Fellow, you will receive:

• Direct mentorship from Anthropic researchers
• Access to a shared workspace in either Berkeley, California or London, UK
• Connection to the broader AI safety and security research community
• A weekly stipend of $3,850 USD / £2,310 GBP / $4,300 CAD, plus benefits
• Funding for compute and other research expenses

The interview process will include an initial application and reference check, technical assessments and interviews, and a research discussion.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

The expected base stipend for this role is $3,850 USD / £2,310 GBP / $4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Fellows will undergo a project selection and mentor matching process. Potential mentors include Alwin Peng and Zygi Straznickas. For a past example of an engineering-heavy project, see 'AI agents find $4.6M in blockchain smart contract exploits'.

Projects in this workstream may include building a CPU simulator for accelerator workloads, adding backends for different accelerators on an open source project, building on demand infrastructure for other infrastructure heavy fellows projects, and building complex synthetic data or environment pipelines.

To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program. Workspace locations are in London and Berkeley, and we are open to remote fellows in the UK, US, or Canada.

We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organisations.

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You will join the multimodal team to push toward superhuman multimodal intelligence. Advance understanding and generation across modalities,image, video, audio, and text,spanning the full stack: data curation/acquisition, tokenizer training, large-scale pre-training, post-training/alignment, infrastructure/scaling, evaluation, tooling/demos, and end-to-end product experiences.

Collaborate cross-functionally with pre-training, post-training, reasoning, data, applied, and product teams to deliver frontier capabilities in multimodal reasoning, world modeling, tool use, agentic behaviors, and interactive human-AI collaboration. Contribute to building models that can see, hear, reason about, and interact with the world in real time at unprecedented levels.

Responsibilities

• Design, build, and optimize large-scale distributed systems for multimodal pre-training, post-training, inference, data processing, and tokenization at web/petabyte scale.
• Develop high-throughput pipelines for data acquisition, preprocessing, filtering, generation, decoding, loading, crawling, visualization, and management (images, videos, audio + text).
• Advance multimodal capabilities including spatial-temporal compression, cross-modal alignment, world modeling, reasoning, emergent abilities, audio/image/video understanding & generation, real-time video processing, and noisy data handling.
• Drive data quality and studies: curation (human/synthetic), filtering techniques, analysis, and scalable pipelines to support trillion-parameter models.
• Create evaluation frameworks, internal benchmarks, reward models, and metrics that capture real-world usage, failure modes, interactive dynamics, and human-AI synergy.
• Innovate on algorithms, modeling approaches, hardware/software/algorithm co-design, and scaling paradigms for state-of-the-art performance.
• Build research tooling, user-friendly interfaces, prototypes/demos, full-stack applications, and enable rapid iteration based on feedback.
• Work across the stack (pre-training → SFT/RL/post-training) to enable reasoning, tool calling, agentic behaviors, orchestration, and seamless real-time interactions.

Basic Qualifications

• Hands-on experience with multimodal pre-training, post-training, or fine-tuning (vision, audio, video, or cross-modal).
• Expert-level proficiency in Python (core language), with strong experience in at least one of: JAX / PyTorch / XLA.
• Proven track record building or optimizing large-scale distributed ML systems (training/inference optimization, GPU utilization, multi-GPU/TPU setups, hardware co-design).
• Deep experience designing and running data pipelines at scale: curation, filtering, generation, quality studies, especially for noisy/real-world multimodal data.
• Strong fundamentals in evaluation design, benchmarks, reward modeling, or RL techniques (particularly for interactive/agentic behaviors).
• Proactive self-starter who thrives in high-intensity environments and is passionate about pushing multimodal AI frontiers.
• Willingness to own end-to-end initiatives and do whatever it takes to deliver breakthrough user experiences.

Preferred Skills and Experience

• Experience leading major improvements in model capabilities through better data, modeling, algorithms, or scaling.
• Familiarity with state-of-the-art in multimodal LLMs, scaling laws, tokenizers, compression techniques, reasoning, or agentic systems.
• Proficiency in Rust and/or C++ for performance-critical components.
• Hands-on work with large-scale orchestration tools such as Spark, Ray, or Kubernetes.
• Background building full-stack tooling: performant interfaces, real-time research demos/apps, or end-to-end product ownership.
• Passion for end-to-end user experience in interactive, real-time multimodal AI systems.

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Zuma is pioneering the future of agentic AI and our focus is to transform the rental market experience for consumers and property managers alike. Our innovative platform is engineered from the ground up to boost operations efficiency and enhance support capabilities for property management business across the US and Canada, a ~$200B market.

Off the back of our Series-A in early 2024, Zuma is scaling rapidly. Achieving our vision requires a team of passionate, innovative individuals eager to leverage technology to redefine customer-business interactions. We're on the hunt for exceptional talent ready to join our mission and contribute to building a groundbreaking technology that reshapes how businesses engage with customers.

As a Staff Engineer, you will:

Help define how humans collaborate with intelligent systems in one of the largest and most underserved industries in the world: property management. You’ll shape the technical foundation of a platform that is not just supporting human workflows, but executing them autonomously through AI agents. This is a rare opportunity to influence how an entire industry evolves, building tools that transform repetitive operational tasks into seamless, intelligent experiences.

Your work will directly contribute to how trust is built between humans and machines, how operations scale without added headcount, and how residents and staff experience a new, AI-powered standard of service. We’re not just building software we’re designing AI that people want to work with. Delightful, trustworthy, and deeply effective.

Join us to help lead the AI revolution in multifamily, drive meaningful real-world impact, and be part of reimagining what work can feel like when done side-by-side with intelligent agents.

You will be a cornerstone of our engineering organization, reporting to the VPE. This is a pivotal role where you'll lead critical system rewrites, architect scalable foundations for our AI platform, and establish the technical standards that will shape our engineering culture for years to come.

You'll work at the intersection of cutting-edge LLM technology and practical business applications, creating sophisticated systems that power our AI leasing agent while building self-serve experiences that enable rapid customer onboarding.

As our first US-based engineer, you'll bridge the gap between our product vision and technical implementation. This role offers a rare opportunity to directly influence how we architect the next generation of our platform.

You'll tackle projects like rebuilding our onboarding/configuration system to be self-serve, creating robust analytics infrastructure to measure AI performance, and reimagining our integration framework to connect seamlessly with customer systems.

Your work will significantly reduce manual engineering overhead while enabling rapid scaling of our customer base.

We're looking for a Staff Engineer to help us bring that future to life. This is not just another dev role. You'll be hands-on shaping the technical DNA of Zuma. You'll architect critical systems, tame legacy code, build net-new AI-powered experiences, and lay down the patterns future engineers will inherit.

If you're obsessed with building real products people use, especially products powered by LLMs, this might be your playground.

Why This Could Be Your Dream Role

• You'll work directly with cutting-edge LLM technology in a real-world application
• You want to work at a company where customers feel your impact every day
• You'll architect AI-powered systems that are transforming the real estate industry
• You'll have autonomy to design and implement innovative technical solutions
• Your work will directly impact thousands of apartment communities and millions of renters
• You'll receive significant equity in a venture-backed company with strong traction
• As we scale, your role and influence will grow with the company

Why You Might Want to Think Twice

• This is a demanding role that will often require extended hours and deep commitment
• As a founding team member, you'll need to wear multiple hats and step outside your comfort zone
• You'll need to make thoughtful tradeoffs between innovation and immediate needs
• You'll interact directly with customers to understand their needs and occasionally travel to their offices
• We're a startup - priorities can shift rapidly as we respond to market opportunities and customer needs
• If you're not comfortable getting your hands dirty with legacy code or speaking directly with customers, this isn't the job for you

Responsibilities

• Lead critical system rewrites to transform our architecture into a highly scalable, resilient foundation
• Own the design and performance optimization of our data storage systems, ensuring they scale with customer and AI demands
• Build and evolve our deployment pipelines, enabling reliable, automated releases for AI-first products
• Set up and manage modern cloud infrastructure from scratch, leveraging Infrastructure as Code (IaC) to ensure consistency, security, and scalability
• Establish engineering best practices, including observability, incident response processes, and system hardening for an AI-first platform
• Drive robust analytics and monitoring to track performance, reliability, and the effectiveness of our AI solutions
• Mentor engineers and elevate the team's capabilities across infrastructure, scalability, and AI product development

Your Experience Looks Like

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
• 5+ years of experience building production-grade software systems, with a focus on scalability, performance, and reliability
• Proven expertise in backend development with Node.js, including API design, system architecture, and cloud-based services
• Experience with cloud infrastructure (AWS, GCP, or similar) and deploying production systems using Infrastructure as Code (e.g., Terraform, Pulumi)
• Hands-on experience with database design, performance tuning, and scaling high-throughput data systems
• Familiarity with building and maintaining CI/CD pipelines, automated testing, and modern DevOps practices
• Strong communication skills and ability to work effectively in a distributed, fast-paced environment
• Comfortable operating in early-stage, high-ownership environments with evolving requirements
• Bonus: Experience with React and TypeScript on the frontend, though this role leans backend/infrastructure
• Bonus: Exposure to LLM-based systems, AI infrastructure, or agentic AI workflows

Guiding Principles

• Customer‑First Outcomes

Every commit should trace back to resident or operator value. Whether it’s a new feature, infra investment, or AI capability, if it doesn’t solve a real problem, it doesn’t ship.

• Bias for Simplicity

We favor composable primitives over clever abstractions. Open standards, clean APIs, and clear contracts win over custom complexity, even if the custom version is cooler.

• Quality Is a Gate, Not an After‑Thought

Quality is built-in from day one. Our definition of done includes: test coverage, performance checks, basic observability, and internal docs. Shipping fast doesn’t mean skipping craftsmanship.

• Data‑Driven Choices

We use data to guide, not paralyze, our decision-making. We track leading indicators (cycle time, defect rate, NPS) and lagging signals (retention, revenue impact). We keep instrumentation lightweight but meaningful signal over spreadsheet.

• Transparency & Written Culture

Good ideas don’t expire in Zoom. We operate in public i

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You'll help property managers succeed with our AI platform while also driving continuous improvements in our internal tools and processes.

Responsibilities: Lead critical system rewrites to transform our architecture into a highly scalable, resilient foundation Own the design and performance optimization of our data storage systems, ensuring they scale with customer and AI demands Build and evolve our deployment pipelines, enabling reliable, automated releases for AI-first products Set up and manage modern cloud infrastructure from scratch, leveraging Infrastructure as Code (IaC) to ensure consistency, security, and scalability Establish engineering best practices, including observability, incident response processes, and system hardening for an AI-first platform Drive robust analytics and monitoring to track performance, reliability, and the effectiveness of our AI solutions Mentor engineers and elevate the team's capabilities across infrastructure, scalability, and AI product development

Your Experience Looks Like: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field 3+ years of experience building production-grade software systems, with a focus on scalability, performance, and reliability Proven expertise in backend development with Node.js, including API design, system architecture, and cloud-based services Experience with cloud infrastructure (AWS, GCP, or similar) and deploying production systems using Infrastructure as Code (e.g., Terraform, Pulumi) Hands-on experience with database design, performance tuning, and scaling high-throughput data systems Familiarity with building and maintaining CI/CD pipelines, automated testing, and modern DevOps practices Strong communication skills and ability to work effectively in a distributed, fast-paced environment Comfortable operating in early-stage, high-ownership environments with evolving requirements Bonus: Experience with React and TypeScript on the frontend, though this role leans backend/infrastructure Bonus: Exposure to LLM-based systems, AI infrastructure, or agentic AI workflows

Guiding Principles: Customer‑First Outcomes Bias for Simplicity Quality Is a Gate, Not an After‑Thought Data‑Driven Choices Transparency & Written Culture

Other Benefits: Great health insurance, dental, and vision Gym and workspace stipends Computer and workspace enhancements Unlimited PTO Opportunity to play a critical role in building the foundations of the company and Engineering culture

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This role goes beyond building models; it's about designing agentic systems, AI-assisted workflows, and data-driven decision engines that help the company scale faster than headcount.

You will be at the forefront of developing the next generation of autonomous systems that power both customer-facing products and internal operations, from optimizing payment experiences to accelerating development, testing, troubleshooting, and product creation.

Responsibilities:

• Architect, build, and deploy LLM-powered applications that augment and automate key workflows across Yuno, from customer service and new product development to internal agentic workflows that optimize critical company processes.

• Design autonomous AI systems that can execute technical analysis, testing, troubleshooting, and decision-making at scale.

• Develop AI-driven tools that create measurable business impact, improving efficiency, accelerating innovation, and driving revenue growth.

Operational Intelligence & Scalability:

• Identify areas across Yuno where AI can generate efficiency gains, reducing manual work, optimizing processes, and enabling smarter operations.

• Build AI systems that enable Yuno to scale without exponential growth in headcount, thereby creating sustainable productivity and organizational intelligence.

Data & Model Optimization:

• Lead fine-tuning and contextual optimization of AI models using Yuno's proprietary data.

• Continuously refine performance through structured feedback loops, observability metrics, and user interaction data.

• Ensure adherence to privacy, compliance, and ethical AI principles in all model development.

Cross-Functional Collaboration & Innovation:

• Work closely with data, product, and infrastructure teams to define the long-term AI roadmap for Yuno.

• Experiment with emerging AI technologies to identify new capabilities that can drive differentiation and strategic advantage.

• Contribute to a culture of experimentation, rapid iteration, and continuous learning across the AI function.

The skills you need:

• 5+ years of professional experience in AI/ML development, with at least 2 years focused on LLMs, RAG, or agentic systems.

• Strong engineering and product mindset, capable of balancing technical depth with strategic impact.

• Exceptional communication and collaboration skills to work across product, engineering, and data functions.

• Passion for pushing the boundaries of applied AI and creating systems that drive real business transformation.

• Willing to work from the Hyderabad office.

Minimum Qualifications:

• LLMs & RAG: Proven experience designing and deploying systems using models like GPT, Claude, Gemini, or similar, including Retrieval-Augmented Generation (RAG) pipelines and contextual retrieval systems.

• AI Agents & Multi-Agent Systems: Hands-on experience with Crew.ai, LangChain, LangGraph, or similar frameworks to build orchestrated agentic workflows.

• Fine-Tuning & Context Engineering: Expertise in supervised fine-tuning (SFT), LoRA, or custom dataset adaptation for domain-specific tasks.

• Programming & Frameworks: Proficiency in Python, GO, and AI/ML libraries such as PyTorch, TensorFlow, or JAX.

• AI Infrastructure: Experience designing scalable, production-ready AI systems in AWS, GCP, or Azure, with a deep understanding of vector databases, model serving, and inference optimization.

• Observability & Monitoring: Familiarity with LangSmith, LangFuse, or equivalent tools for tracking, debugging, and evaluating LLM performance.

• API Integration: Expertise in integrating AI systems with RESTful APIs and internal platforms to create seamless, usable products.

Preferred Qualifications:

• Experience using LlamaIndex, Hugging Face, or similar open-source frameworks.

• Strong understanding of context optimization, embedding strategies, and knowledge retrieval.

• Familiarity with MLOps, CI/CD pipelines, and production deployment best practices.

• Prior experience in fintech, payments, or other data-intensive and regulated industries.

• Analytical rigor and ability to translate business objectives into measurable AI outcomes.

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You will serve as the focal point for all technical matters related to thrust vectoring, ensuring the system enables precise flight control authority, integrates cleanly with the engine and airframe, and performs reliably across the full range of operational conditions. This role is hands-on, data-driven, and highly cross-functional, requiring collaboration with controls, airframe, flight test, and mission teams.

Responsibilities:

• Act as the single-threaded owner for the TVC system, accountable for all technical decisions from concept to flight.
• Define and manage system requirements, performance goals, and mechanical/electrical interfaces.
• Design and integrate vectoring mechanisms with the engine and surrounding structure.
• Lead ground and flight testing of the TVC system, including instrumentation planning, data collection, and performance evaluation.
• Analyze control authority, vectoring bandwidth, and dynamic response across the flight envelope.
• Collaborate with the controls team to shape vectoring logic and ensure closed-loop system performance meets CONOPS requirements.
• Own fault management, failure investigations, and system reliability strategies.
• Represent the TVC system in design reviews, technical checkpoints, customer briefings, and leadership updates.

Qualifications:

• Bachelor's degree in aerospace engineering, Mechanical Engineering, or a related discipline.
• 7+ years of experience in aerospace propulsion or flight control systems, with relevant experience owning subsystem development.
• Deep understanding of nozzle dynamics, actuation systems, mechanical integration, and structural/thermal constraints.
• Demonstrated experience in hardware development, test planning, and flight test support.
• Strong proficiency in Python for performance analysis, data processing, and model correlation.
• Familiarity with tools such as ANSYS, FEA, or thermal/fluid modeling for mechanism and system validation.
• U.S. Citizenship or ability to comply with ITAR requirements.

Preferred Qualifications:

• Experience with TVC or control effector systems on UAVs, tactical aircraft, or rocket platforms.
• Familiarity with low-bypass turbofan engines and integration constraints near hot-end propulsion hardware.
• Experience collaborating on control logic development, transient response shaping, and actuator tuning.
• Proficiency with Siemens NX and Teamcenter for CAD and configuration control.
• Background in failure modes analysis, margin modeling, and system validation strategies.
• M.S. or Ph.D. in Aerospace Engineering or a related discipline.

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The ideal candidate will possess deep expertise in integrating mechanical, electronic, and software systems into complex optical products. This role will involve leading the design and development of high-performance optical devices from concept through production, ensuring precision, reliability, and manufacturability.

Responsibilities:

• Lead the mechanical and electromechanical design of complex optical systems.
• Collaborate closely with optical, electrical, and software engineers and suppliers to ensure system-level integration and performance optimization.
• Conduct tolerance analysis, thermal and vibration studies to ensure optical alignment stability and reliability.
• Support prototype build, testing, and design iteration cycles.

• Design and integrate sensors, control systems, and embedded components to enable automated alignment, focusing, and calibration of optical systems.
• Develop and refine feedback and control algorithms for mechatronic subsystems.

• Serve as a technical lead in cross-functional teams, guiding junior engineers and technicians.
• Define system requirements, design specifications, and validation protocols for mechatronic subsystems.
• Interface with manufacturing and supply chain teams to support design-for-manufacturing (DFM) and design-for-assembly (DFA) initiatives.

• Design and oversee qualification testing of mechatronic components and optical assemblies.
• Implement quality and reliability assessments throughout the design cycle.

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We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid's network covers 12,000 financial institutions across the US, Canada, UK and Europe.

The AI Applications Team You will have the opportunity to join as one of the founding members of this newly formed team that is dedicated to consolidating and rapidly scaling our successful bets so far, and grow with the team in our quest to accelerate Plaid's transformation into an AI-first company.

In this role you will lead projects that enable and scale our business with our largest AI customers and partners, starting with personal finance use cases and expanding into many others; examples include:

• Develop and evolve the preferred integration pattern for Plaid with AI providers - from API adaptations to building the official Plaid MCP Servers, and beyond

• Redefine how Plaid's consumer link experience embed into conversational interfaces in the most seamless way

• Architect the trust layer for the future of agentic commerce that will become the industry standard

Additionally you will be expected to scale and extend our existing successful bets on AI-powered customer experience; examples include:

• Make the next step-function improvement in our homegrown customer support agent

• Land our multi-turn and multi-agent system that powers a truly delightful experience for our customers; define how to scalably run offline evaluation for complex multi-turn open-ended tasks; research and prototype how Human-In-The-Loop - Reinforcement Learning (RLHF) can power an insights flywheel; pioneer the architecture for customer-specific long-term memory, etc.

• Extend our agentic system to support other critical parts of the customer journey, starting with areas with the highest ROI - top-of-funnel product recommendation, customer onboarding and risk diligence, customer activation and assistance for faster productionization, as well as upselling and cross-selling of Plaid products

You will have a front row seat to all the latest industry developments. Over time, with the skills and experience you develop and hone on this team, you can become an influential voice in defining where AI < Fintech will be heading longer term.

Responsibilities

• Build across the stack. Design, develop, and maintain scalable backend services and APIs, as well as intuitive, high-quality frontend applications that bring those systems to life.

• Work with other AI engineers, software engineers and machine learning engineers to architect, design and implement GenAI-powered products and features

• Collaborate across functions to understand user needs, propose and implement AI-powered solutions where they’re expected to have the highest impact

• Design and execute rapid experiments to push the boundaries on potential business impact from emerging AI capabilities, with a focus on minimal viable testing approaches

• Balance creative exploration of possibilities with rigorous evaluation of technical feasibility, product potential and business impact

Requirements

• Experience building backend services and working with microservices or service-oriented architectures

• Strong working knowledge of HTML, CSS, JavaScript, and modern frontend frameworks or libraries, with comfort building user-facing experiences

• Hands-on experience working with LLMs to build products and shipping them to product with iterating with real user feedback - including but not limited to:

• Prompt engineering

• Fine-tuning

• Retrieval augmented generation (RAG)

• Semantic search

• Vector database and embedding models

• Agent orchestration framework

• Evaluation and monitoring framework of open-ended tasks

• Streaming and SSE

• Common UX and design patterns for GenAI-powered products

• Strong debugging and monitoring experience for production systems

• Ability to deeply understand customer and user needs through user research and rapid experimentation - be your own technical PM

• Ability to balance divergent thinking (exploring possibilities) with convergent thinking (evaluating feasibility), which is critical for driving 0 ->1 projects

• Extremely curious and passionate about working in GenAI applications space

Nice-to-Haves

• Experience training and/or serving ML models in production, or fine-tuning LLMs for domain-specific use cases

• Comfortable operating in privacy/PII-sensitive environments and applying compliance mitigations

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As a Solutions Engineer, you will partner with Sales and Customer Engineering throughout the pre-sales and post-sales journey as the technical expert helping customers solve their most challenging database problems. You will lead technical discovery to match customers' business and technical objectives with PlanetScale's offerings. You will design and execute proof of value timelines that deliver on agreed-upon business outcomes and success criteria. You will design database migration strategies and work hands-on with customers to execute migrations to PlanetScale's PostgreSQL and Vitess platforms. You will assess workloads, analyze performance requirements, and recommend architecture, sizing, and optimization strategies. You will build tools, scripts, and automation that accelerate migrations and improve customer onboarding. You will create educational content including documentation, guides, blog posts, workshops, and videos. You will collaborate with Product and Engineering teams to advocate for customer needs and shape the platform.

You have deep expertise in database systems including replication, high availability, sharding, performance tuning, and migration strategies. You are equally comfortable presenting architecture designs to executives and writing scripts to automate migration tasks. You thrive in customer-facing situations and translate technical concepts into business value for diverse audiences. You are self-motivated and can manage multiple engagements simultaneously with minimal oversight. You enjoy creating content and sharing knowledge through various formats. You are comfortable with occasional travelmaxcdn< 20%.

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We are seeking an experienced Enterprise Support Engineer to join our core engineering team. As an Enterprise Support Engineer, you will advise and handle support requests from enterprise customers on the PlanetScale platform.

Responsibilities:

• Advise and handle support requests from enterprise customers on the PlanetScale platform.
• Become a customer-facing subject-matter expert for enterprise customers on the PlanetScale platform.
• Identify product gaps in a customer-specific context and work with Technical Account Management, Engineering and Sales Engineering teams to prioritize and escalate them.
• Be part of an on-call rotation for high-priority issues.

Requirements:

• Experience supporting production databases and applications, preferably at scale.
• Experience with database internals and performance tuning, specifically for PostgreSQL and MySQL databases.
• Working knowledge of Kubernetes.
• Strong ability to communicate and deal directly with customers, whether in email, Slack, video conference, or in person.

Nice to Have:

• Knowledge of common application deployment platforms and frameworks, such as Python, Go, Node, PHP.
• Experience with cloud platforms (AWS, GCP, Azure).
• Knowledge of monitoring, observability, and debugging tools.
• Contributions to open-source projects, especially in the database or infrastructure space.

Why PlanetScale?

We're redefining how high-growth companies manage data at scale,and we work with some of the most exciting brands in gaming, consumer tech, and B2B SaaS. As a Software Engineer, you'll be at the core of building the platform that powers world-class apps used by hundreds of millions of users worldwide. PlanetScale is a profitable company with a philosophy centered around building small teams of p99 individuals and is recognized as one of the fastest-growing companies in America.

Total Compensation and Pay Transparency

An employee's total compensation consists of base salary + variable comp where appropriate + benefits + equity. A member of our Talent Acquisition team will be happy to answer any further questions when we engage with you to begin the interview process.

Salary Range: US $120,000 - $200,000

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Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use.

Responsibilities

• Build across the stack. Design, develop, and maintain scalable backend services and APIs, as well as intuitive, high-quality frontend applications that bring those systems to life.
• Work with other AI engineers, software engineers and machine learning engineers to architect, design and implement GenAI-powered products and features
• Collaborate across functions to understand user needs, propose and implement AI-powered solutions where they’re expected to have the highest impact
• Design and execute rapid experiments to push the boundaries on potential business impact from emerging AI capabilities, with a focus on minimal viable testing approaches
• Balance creative exploration of possibilities with rigorous evaluation of technical feasibility, product potential and business impact

Qualifications

• Experience building backend services and working with microservices or service-oriented architectures
• Strong working knowledge of HTML, CSS, JavaScript, and modern frontend frameworks or libraries, with comfort building user-facing experiences
• Strong software engineering fundamentals, including system design and API development
• Hands-on experience building and shipping LLM-powered products, iterating with real user feedback
• Practical experience with prompt engineering, fine-tuning, RAG, semantic search (vector databases and embeddings), agent orchestration frameworks, and evaluation/monitoring of open-ended tasks
• Experience building GenAI-powered product experiences, including streaming/SSE and common UX patterns
• Strong debugging and production monitoring experience
• Ability to deeply understand customer needs through user research and rapid experimentation; comfortable operating as a technical PM when needed
• Ability to balance divergent exploration with pragmatic execution, especially in 0 to 1 environments
• Deep curiosity and passion for building GenAI applications

Nice to Have

• Experience training and deploying ML models in production, including fine-tuning LLMs for domain-specific use cases
• Comfortable operating in privacy- and PII-sensitive environments, with experience applying appropriate compliance and data protection controls

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We believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

Role Summary

You will be in charge of open-sourcing state-of-the-art models, whilst maintaining and improving Mistral’s publicly available libraries. Your work is critical in helping turn research breakthroughs into tangible solutions and improve Mistral's open-source ecosystem.

Responsibilities

• Releasing our models to open-source platforms and libraries, e.g., vLLM, GitHub, Hugging Face • Maintaining Mistral’s open-source libraries (mistral-common, mistral-finetune, mistral-inference) • Create and maintain tooling and services: both internal facing (internal research) and external facing (open-source libraries) • Implement and optimize open-source and internal libraries for performance and accuracy, ensuring production readiness and employing cutting-edge technology and innovative approaches • Collaborate with the open-source community (PyTorch, vLLM, Hugging Face)

About You

• Master’s degree in Computer Science, Machine Learning, Data Science, or a related field • Experience contributing to popular open-source libraries such as PyTorch, Tensorflow, JAX, vLLM, Transformers, Llama.cpp, ... • Passion for contributing to the open-source software ecosystem • Expert programming skills in Python, PyTorch, MLOps • Adaptable, proactive, and autonomous • Attention to detail and a drive to go the last mile to build almost perfect tools • Deep understanding of machine learning approaches, especially LLMs and algorithms • Low-ego, collaborative and have a real team player mindset

Now, it would be ideal if you have:

• Experience with training and fine-tuning large language models (e.g., distillation, supervised fine-tuning, policy optimization) • Experience working with Slurm • Worked with research teams before • Experience as a core-maintainer of a popular ML open-source library

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Forge turns cutting-edge research into enterprise-ready capabilities by powering model fine-tuning, reinforcement learning and post-training workflows. By working at the intersection of research and product it provides customers with the tools to train specialized models that deliver real-world business value.

As the PM leading Forge you will shape a 0-1 product with significant business impact and the potential to grow offering while defining how organizations train and deploy the next generation of AI models.

Key Responsibilities:

Define the Future • Set the vision: Shape and evangelize a compelling product strategy for Forge ensuring alignment with company goals and market opportunities.

Spot the gaps: Lead market and UX research to uncover unmet needs, competitive whitespaces, and emerging trends in SOTA AI post-training capabilities.

Build & Ship • Own the lifecycle: Drive end-to-end product development, from ideation to launch and iteration,balancing speed, quality, and user delight.

Champion the user: Partner with design and research to craft intuitive, high-impact experiences, using data and feedback to refine continuously.

Scale, Execute, & Enable • Go-to-market: Collaborate with marketing and sales to launch products successfully, including pricing, positioning, and adoption strategies.

Align stakeholders: Rally engineering, design, and business teams around priorities, trade-offs, and timelines.

Prioritize ruthlessly: Maintain a dynamic roadmap that delivers quick wins while advancing long-term bets.

Requirements:

Product Management Experience 5+ years of relevant experience in new, competitive, fast-paced and ambiguous environments with a track record of building and scaling complex AI/ML or infrastructure solutions.

Technical skills - Very good understanding of training pipelines, RL loops, and model deployment architectures,

Expertise in AI model lifecycle management, including fine-tuning, evaluation, and serving.

Experience with Infrastructure as Code (IaC), containerization, and scalable deployment modes (e.g., on-prem, VPC, cloud).

Familiarity with Kubernetes/Slurm is a strong plus.

User obsession Relentless focus on solving real user problems, backed by data and qualitative insights.

Cross-functional influence Proven ability to align and inspire engineering, design, and go-to-market teams without direct authority.

Problem-solving Balance big-picture thinking with hands-on problem-solving , you’re equally comfortable crafting a roadmap, diving into metrics and running technical tests.

Communication: Crisp, persuasive storytelling for executives, teams, and users , ability to distill complex technical concepts (e.g., RL, LoRA, SFT) into clear narratives for docs, decks, and workshops.

Adaptability: Thrive in high-velocity, dynamic settings where priorities shift quickly.

Collaboration: Low ego + high EQ , you build trust and drive decisions through clarity, not hierarchy.

Autonomy: Self-directed with a bias for action, you own outcomes end-to-end.

Preferred Qualifications:

Infrastructure knowledge - Strong knowledge of model training, model architectures, etc.

Strong understanding how complex architectures are designed and impact of deployment modes

Proficient coding skills are strongly recommended

Kubernetes know-how strongly recommended

Growth mindset: Deep familiarity with product-led growth strategies (e.g., viral loops, onboarding optimization, monetization, etc.).

Builder’s mindset: Founder or early-stage PM experience , you’ve turned 0 → 1 ideas into products users love.

Technical depth: Ability to prototype, hack, or dive into code when needed.

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As a Senior Software Engineer - Stability, you will lead projects end-to-end, drive technical projects from concept to production. You will define solutions, analyze tradeoffs, make critical decisions, and deliver software that works today and is sustainable for tomorrow.

Key responsibilities include:

• Championing reliability by making technical choices that improve the reliability of Mercury's systems and making it easier to get reliability by default.
• Measuring outcomes by defining and collecting metrics that show how your work creates value for the business.
• Approaching code with craft by writing clear, testable, and maintainable code.
• Building for quality and sustainability by designing extensible systems, making balanced decisions on tech debt, planning careful rollouts, and owning the quality of your work through post-launch monitoring.
• Improving the developer experience by approaching problems with a product mindset, getting close to internal customers by supporting them and getting feedback from them.

The ideal candidate for this role has expertise in PostgreSQL with query optimization, tuning, replication, pooling/proxying, or client-side libraries. They have worked with other data systems supporting a relational database: event streaming, OLAP, caches, etc. They have authored and operated Temporal workflows, are familiar with tracing and OpenTelemetry, and have learned by leading moderate-to-large technical projects, including planning, execution, and stakeholder management.

The salary range for this role is $166,600 - 250,900 for US employees and CAD $157,400 - 237,100 for Canadian employees.

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Responsibilities

• You'll individually help deploy into production use cases with a considerable business impact across various industries.
• You'll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving technological transformation with our customers.
• You'll work in collaboration with our researchers, other AI engineers, product engineers on complex customer projects involving fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases.
• You'll холод involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations.
• You will provide technical guidance on our products and explain Mistral technologies to various stakeholders.
• Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers' feedback

How We Work in Applied AI

• We care about people and outputs.
• What matters is what you ship, not the time you spend on it.
• Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to.
• The best idea wins, whether it comes from a principal engineer or someone in their first week.
• Always ask why. The best solutions come from deep understanding, not from copying what worked before.
• We say what we mean. Feedback is direct, timely, and given because we care.
• No politics. Low ego, high standards.
• We embrace an unstructured environment and find joy in it.

About You

• You are fluent in English.
• You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products.
• You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces.
• You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases.
• You have deep understanding of concepts and algorithms underlying machine learning and LLMs.
• You have strong technical coding skills in Python.
• You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences.

Ideally You Have:

• Contributed to open-source projects in particular in the space of LLMs.
• Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager.
• You have experience with deep learning with PyTorch

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At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We are seeking a Applied AI Engineer to facilitate the adoption of our products among customers and collaborate with them to address complex technical challenges. The Applied AI Engineer will be an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products.

Responsibilities

• Onboard customers on our products and APIs, providing guidance on prompting, evaluation, and fine-tuning, and ensuring the best production integration with back-end and front-end interfaces.

• Work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation.

• Individually help deploy into production use cases with a considerable business impact across various industries.

• Collaborate with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open source codebases for tasks such as inference and fine-tuning.

• Be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. Provide technical guidance on our products and explain Mistral technologies to various stakeholders.

About You

• You are fluent in English.

• You hold a PhD / master in AI / data science.

• You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products.

• You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases.

• You have a deep understanding of concepts and algorithms underlying machine learning and LLMs.

• You're experienced with building and deploying LLMs or NLP applications.

• You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces.

• You have strong technical coding skills in Python.

• You have experience with deep learning with Pytorch.

• You have experience with agents framework such as Langchain, vector DBs.

Ideally You Have:

• Contributed to open-source projects in particular in the space of LLMs.

• Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager.

Benefits

• Competitive salary.

• Generous Equity.

• Health: Sun Life.

• Pension: Match up to 6% of your contributions.

• PTO: 25 days.

• Transportation: Allowance public transportation or Parking charges reimbursed.

• Coaching: we offer Betterup coaching on a voluntary basis.

• Sport: 145 CAD/month reimbursement for gym membership.

• Meal stipend: 480 CAD monthly allowance for meals (solution might evolve as we grow bigger).

By applying, you agree to our Applicant Privacy Policy.

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Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. The Applied AI Engineer will be an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products.

Responsibilities

• Onboard customers on our products and APIs, providing guidance on prompting, evaluation, and fine-tuning, and ensuring the best production integration with back-end and front-end interfaces.

• Work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation.

• Individually help deploy into production use cases with a considerable business impact across various industries.

• Collaborate with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open source codebases for tasks such as inference and fine-tuning.

• Involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. Provide technical guidance on our products and explain Mistral technologies to various stakeholders.

• Collaboration with our product and science team to improve continuously our product and model capabilities based on customers' feedback

About You

• You are fluent in English.

• You hold a PhD / master in AI / data science.

• You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products.

• You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases.

• You have deep understanding of concepts and algorithms underlying machine learning and LLMs.

• You're experienced with building and deploying LLMs or NLP applications.

• You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces.

• You have strong technical coding skills in Python.

• You have experience with deep learning with Pytorch.

• You have experience with agents framework such as Langchain, vector DBs.

Benefits

• Competitive salary and bonus structure.

• Generous Equity.

• Health: Competitive Healthcare program (Medical Provider: Blueshield of California 100% coverage for employee, 75% for dependents).

• Pension: 401K (6% matching).

• PTO: 18 days.

• Transportation: Reimburse office parking charges, or $120/month for public transport.

• Coaching: we offer Betterup coaching on a voluntary basis.

• Sport: $120/month reimbursement for gym membership.

• Meal stipend: $400 monthly allowance for meals (solution might evolve as we grow bigger).

• Visa sponsorship

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We're seeking an Applied AI Engineer to facilitate the adoption of our products among customers and collaborate with them to address complex technical challenges.

The Applied AI team is Mistral's customer-facing technical organisation. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.

Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution.

By joining the team, you'll bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision.

Responsibilities

• You'll individually help deploy into production use cases with a considerable business impact across various industries.
• You'll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation.
• You'll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases for tasks such as inference and fine-tuning.
• You'll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders.
• Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers' feedback

How We Work in Applied AI

• We care about people and outputs.
• What matters is what you ship, not the time you spend on it.
• Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week.
• Always ask why. The best solutions come from deep understanding, not from copying what worked before.
• We say what we mean. Feedback is direct, timely, and given because we care.
• No politics. Low ego, high standards.
• We embrace an unstructured environment and find joy in it.

About You

• You are fluent in English.
• You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products.
• You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces.
• You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases.
• You have deep understanding of concepts and algorithms underlying machine learning and LLMs.
• You have strong technical coding skills in Python.
• You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences.

Ideally you have:

• Contributed to open-source projects in particular in the space of LLMs.
• Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager.
• You have experience with deep learning with Pytorch

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At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We are seeking a Applied AI Engineer to facilitate the adoption of our products among customers and collaborate with them to address complex technical challenges. The Applied AI Engineer is an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products and building complex enterprises use-cases.

Responsibilities

• You'll individually help deploy into production use cases with a considerable business impact across various industries.
• You'll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation.
• You'll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning.
• You'll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders.
• Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback

About you

• You are fluent in English
• You hold a PhD / master in AI / data science or you’re self-made
• You have 7-10+ years as a technical individual contributor (data scientist or software engineer) on AI-based products
• You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases
• You have deep understanding of concepts and algorithms underlying machine learning and LLMs
• You have a deep understanding of Cloud Infrastructure and how to deploy AI based products
• You have deployed or built products with large scale user based
• You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences

Benefits

• Competitive cash salary and equity
• Health Insurance
• Sport: $90 for gym membership allowance
• Food: $200 monthly allowance for meals (solution might evolve as we grow bigger)
• Transportation: $120/month for public transport or Parking charges reimbursed

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At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We are a company that democratizes AI through high-performance, optimized, open-source and cutting-edge models, products, and solutions. Our offerings include le Chat, the AI assistant for life and work.

About The Job

Mistral AI is seeking a Technical Lead, Applied AI to drive the technical strategy, execution, and delivery of complex AI solutions for our enterprise customers. In this role, you will lead a project teams of Applied AI Engineers, ensuring the successful deployment of Mistral AI products and the development of high-impact, scalable AI use cases.

Responsibilities

• Deliver as an IC the critical lines of codes of our complex projects, you’ll be hands-on and de-risk the critical parts of our complex projects. You’ll stay deeply involved in coding, reviewing, and optimizing AI solutions.

• Lead technical teams of Applied AI Engineers, providing mentorship, technical guidance, and best practices for deploying state-of-the-art GenAI applications across industries.

• Lead technical discussions during pre-sales, translating customer requirements into actionable solutions and communicating Mistral’s technological advantages to diverse stakeholders.

• Design and oversee the implementation of complex AI systems, including fine-tuning, RAG, agentic workflows, and custom LLM applications, ensuring alignment with Mistral’s product roadmap and open-source initiatives.

• Drive innovation by identifying emerging trends in AI, evaluating new tools and methodologies, and championing best practices for fine-tuning, inference, and deployment.

• Work closely with product managers, researchers, and engineers to ensure seamless integration of customer feedback into Mistral’s product development cycle.

How We Work in Applied AI

• We care about people and outputs.

• What matters is what you ship, not the time you spend on it

• Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week.

• Always ask why. The best solutions come from deep understanding, not from copying what worked before

• We say what we mean. Feedback is direct, timely, and given because we care.

• No politics. Low ego, high standards.

• We embrace an unstructured environment and find joy in it.

About You

• You are fluent in French and English.

• You hold a PhD or Master’s degree in AI, Machine Learning, Computer Science, or a related field.

• You have 7/8+ years of experience in AI/ML, with at least 2+ years in a technical leadership role (e.g., Tech Lead, Engineering Manager, Staff Engineer or Solutions Architect) focused on AI products or enterprise solutions.

• You have a proven track record of leading teams to deliver complex AI projects, from prototyping to production, in industries such as tech, finance, healthcare, or industrial automation.

• You possess deep expertise in fine-tuning LLMs, advanced RAG, agentic systems, and deploying NLP applications at scale.

• You are proficient in Python, PyTorch, and modern AI frameworks (e.g., LangChain, Hugging Face).

Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools is a plus.

• You have strong software engineering skills, including API design, backend/full-stack development, and system architecture.

• You excel in technical communication, with the ability to articulate complex concepts to both technical and non-technical audiences, including executives and engineers.

• You thrive in fast-paced, collaborative environments and are passionate about mentoring and growing technical talent.

Ideally, you have:

• Contributed to open-source projects, particularly in the LLM or AI space.

• Experience in customer-facing roles (e.g., Solutions Architect, Customer Engineer, or Technical Product Manager) with a focus on enterprise AI adoption.

• A track record of driving technical strategy and influencing product direction based on customer needs and market opportunities.

Why Join Us?

You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you!

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We are seeking an AI Scientist to join our research team in Warsaw. As an AI Scientist, you will research and develop novel methods to push the frontier of large language models, work across use cases and modalities, and build tooling and infrastructure to allow training, evaluation, and analysis of AI models at scale.

Responsibilities

• Research and develop novel methods to push the frontier of large language models • Work across use cases (e.g., reasoning, code, agents) and modalities (e.g., text, image, and speech) • Build tooling and infrastructure to allow training, evaluation, and analysis of AI models at scale • Work cross-functionally with other scientists, engineers, and product teams to ship AI systems that have a real-world impact

About You

• You are a highly proficient software engineer in at least one programming language (Python or other, e.g., Rust, Go, Java) • You have hands-on experience with AI frameworks (e.g., PyTorch, JAX) or distributed systems (e.g., Ray, Kubernetes) • You have high engineering competence. This means being able to design complex software and make it usable in production • You are a self-starter, autonomous, and a team player

Benefits

• Competitive cash salary and equity • Food: Monthly meal allowance • Sport: Monthly contribution to a Gympass subscription • Private pension plan

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At Mistral, we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.

We develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit.

What will you do?

• Research and develop novel methods to push the frontier of large language models
• Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)
• Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale
• Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact

About you

• An expert in speech input/output methodologies (specific to audio)
• Highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)
• Hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)
• High engineering competence. This means being able to design complex software and make it usable in production
• Self-starter, autonomous and a team player

Now, it would be ideal if

• You have experience working with large-scale speech-language models
• You have hands-on experience with training large transformer models in a distributed fashion
• You can navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment
• You have a strong publication record in a relevant scientific domain

Benefits

France

• Competitive cash salary and equity
• Food: Daily lunch vouchers
• Sport: Monthly contribution to a Gympass subscription
• Transportation: Monthly contribution to a mobility pass
• Health: Full health insurance for you and your family
• Parental: Generous parental leave policy

UK

• Competitive cash salary and equity
• Insurance
• Transportation: Reimburse office parking charges, or 90GBP/month for public transport
• Sport: 90GBP/month reimbursement for gym membership
• Meal voucher: £200 monthly allowance for its meals
• Pension plan: SmartPension (percentages are 5% Employee & 3% Employer)

XML job scraping automation by YubHub

At Mistral, we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.

We develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit.

Responsibilities

• Research and develop novel methods to push the frontier of large language models
• Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech)
• Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale
• Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact

About You

• You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java)
• You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes)
• You have high engineering competence. This means being able to design complex software and make it usable in production
• You are a self-starter, autonomous and a team player

Now, it would be ideal if

• You have hands-on experience with training large transformer models in a distributed fashion
• You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment
• You have a strong publication record in a relevant scientific domain
• Audio/Speech experience - audio input/out, NLP

What We Offer

• Competitive salary and bonus structure
• Generous Equity
• Health: Competitive Healthcare program (Medical Provider: Blueshield of California 100% coverage for employee, 75% for dependents)
• Pension: 401K (6% matching)
• PTO: 18 days
• Transportation: Reimburse office parking charges, or $120/month for public transport
• Coaching: we offer Betterup coaching on a voluntary basis
• Sport: $120/month reimbursement for gym membership
• Meal stipend: $400 monthly allowance for meals (solution might evolve as we grow bigger)
• Visa sponsorship

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About the company: The mining industry has steadily become worse at finding new ore deposits, requiring >10X more capital to make discoveries compared to 30 years ago. KoBold Metals builds AI models for mineral exploration and deploys those models,alongside our novel sensors,to guide decisions on KoBold-owned-and-operated exploration programs.

About The Role: In this role, you will partner with exploration and engineering teams to build reliable, scalable infrastructure that makes it easier to turn data and models into real-world exploration insights. You will improve observability, streamline MLOps workflows, and maintain shared tools like JupyterHub that enable faster experimentation and collaboration. Your work will help create a solid foundation for scientists and engineers to focus on discovery instead of infrastructure.

Responsibilities

• Design, build, and operate compute infrastructure that is both scalable and reliable to support critical services.
• Work closely with engineering teams to embed observability, reliability, and security throughout the software development process.
• Create and maintain automation for monitoring, deployments, and incident response to keep operations efficient and predictable.
• Lead or support capacity planning, performance reviews, and system tuning to ensure stable and efficient systems.
• Join the on-call rotation and take part in incident response, troubleshooting, and resolution.
• Develop and refine monitoring and alerting to catch issues early and reduce downtime.
• Establish and maintain disaster recovery and business continuity practices that protect the organization against failures.
• Regularly review and improve our tools and processes to strengthen system visibility and reliability.
• Investigate points of fragility in distributed systems and understand how complex systems behave under stress in order to improve resilience.
• Continually learn about mineral exploration through reading, discussions with exploration team members, periodic rotation on an exploration team and time in the field with geologists

Qualifications

• 5+ years of experience as an Infrastructure Engineer, Site Reliability Engineer or in a similar role
• Strong scripting and programming skills (Python, Go, Java or JavaScript/ Node.js )
• Experience with IaC tools like Terraform and container orchestration tools like Kubernetes and Docker
• Experience with cloud platforms such as AWS
• Experience operating or administering JupyterHub in a multi-user environment
• Understanding of MLOps workflows, including model training, deployment, and related tooling
• Excellent communication & collaboration skills and a continuous improvement mindset
• Proven ability to troubleshoot complex issues and implement effective solutions
• Proven ability to thrive in dynamic and evolving environments, effectively navigating uncertainty and incomplete information.
• Proven ability to grow expertise, influence & educate others
• Comfortable making informed decisions with limited data, adapting quickly to new circumstances, and maintaining focus on strategic objectives while driving clarity for the team.
• Intellectual curiosity and eagerness to learn about all aspects of mineral exploration, particularly in the geology domain. Enjoys constantly learning such that you are driving insights through using our tools in exploration and willing to work directly with geologists in the field.
• Ability to explain technical problems to and collaborate on solutions with domain experts who are not infrastructure engineers. A strong communicator who enjoys working with colleagues across the company.
• Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on an evolving range of responsibilities.
• Keen not just to build cool technology, but to figure out what technical product to build to best achieve the business objectives of the company.

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This role will support compliance management in reviewing new products and services to ensure they are compliant with BSA/AML and consumer protection regulations and understanding the types of controls that would be needed in order to mitigate AML risk. Most importantly, they will serve as our growing department’s ‘lead,’ offering support and expertise in financial crimes compliance.

Your day-to-day:

• Own and optimize AML transaction monitoring and screening systems (e.g., rules tuning, threshold adjustments, alert calibration).
• Analyze alert and case data to identify trends, gaps, and opportunities to improve detection efficiency and effectiveness.
• Investigate and clear transaction monitoring alerts.
• Partner with Product, Data, and Engineering teams to design, implement, and enhance AML controls.
• Act as the primary point of contact for AML vendors, managing system performance, enhancements, and issue management.
• Conduct ongoing validation and testing of monitoring scenarios to ensure alerts are accurate, risk-aligned, and defensible.
• Support model/rule governance, including documentation, tuning rationale, and audit/regulatory readiness.
• Perform quality assurance on alerts, cases, and SAR/UAR outputs to ensure consistency and regulatory compliance.
• Contribute to the development and enhancement of AML policies, procedures, and risk assessments.
• Assist with audits, regulatory exams, and internal reviews related to transaction monitoring and screening systems.
• Identify and drive automation and process improvements across AML operations and systems.
• Support ad-hoc analyses and strategic initiatives as Greenlight scales.

What you’ll bring to the team:

The position will be fast-paced with no day being the same as the one before, so we are looking for a fun, energetic individual who is passionate about financial crimes and compliance in addition to the below:

• 5–7 years of AML/BSA/CTF experience within a bank, fintech, or money services business.
• Strong hands-on experience with AML systems (transaction monitoring and/or screening), including rules tuning, scenario development, or alert optimization.
• Demonstrated experience working with AML data (alert volumes, false positives, typologies, segmentation, etc.).
• Experience working with or managing third-party AML vendors (e.g., ComplyAdvantage, Oscilar, Actimize, Verafin, etc.).
• Familiarity with model/rule validation, tuning methodologies, and/or system implementation is strongly preferred.
• CAMS, CFE, or similar certification preferred.
• Solid understanding of BSA/AML regulations, OFAC, and suspicious activity reporting requirements.
• Ability to translate regulatory requirements and risk insights into practical system rules and controls.
• Strong analytical mindset with experience using data to drive decisions (SQL or data tooling is a plus, but not required).
• Comfortable working cross-functionally with technical and non-technical stakeholders.
• Ability to operate independently in a fast-paced, evolving environment.

Work perks at Greenlight:

• Medical, dental, vision, and HSA match
• Paid life insurance, AD&D, and disability benefits
• Traditional 401k with company match
• Unlimited PTO
• Paid company holidays and pop-up bonus holidays
• Professional development stipends
• Mental health resources
• 1:1 financial planners
• Fertility healthcare
• 100% paid parental and caregiving leave, plus cleaning service and meals during your leave
• Flexible WFH, both remote and in-office opportunities
• Fully stocked kitchen, catered lunches, and occasional in-office happy hours
• Employee resource groups

Additional Information

Our stance on salaries: Greenlight provides a competitive compensation package with a market-based approach to pay and will vary depending on your location, experience and skill set. The total compensation package for this position will also include a discretionary performance bonus, equity rewards, medical benefits, 401K match, and more.

Greenlight conducts continuous compensation evaluations across departments and geographies to ensure we are keeping our pay current and competitive.

The estimated base pay range for this position in (NY, CA, WA): $60,000 - $80,000

The estimated base pay range for this position in (CO): $60,000 - $70,000

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Based in Mountain View, CA, Cyngn is a publicly-traded autonomous technology company that deploys self-driving industrial vehicles to factories, warehouses, and other facilities throughout North America.

We are looking for innovative, motivated, and experienced leaders to join us and move this field forward. If you like to build, tinker, and create with a team of trusted and passionate colleagues, then Cyngn is the place for you.

Key reasons to join Cyngn:

• We are small and big. With under 100 employees, Cyngn operates with the energy of a startup. On the other hand, we’re publicly traded. This means our employees not only work in close-knit teams with mentorship from company leaders,they also get access to the liquidity of our publicly-traded equity.

• We build today and deploy tomorrow. Our autonomous vehicles aren’t just test concepts,they’re deployed to real clients right now. That means your work will have a tangible, visible impact.

• We aren’t robots. We just develop them. We’re a welcoming, diverse team of sharp thinkers and kind humans. Collaboration and trust drive our creative environment. At Cyngn, everyone’s perspective matters,and that’s what powers our innovation.

About this role:

Cyngn is building a cloud platform that helps customers monitor, manage, and optimize fleets of autonomous industrial vehicles in real time. As a Full Stack Engineer (Mid–Senior), you’ll ship features end-to-end,from Python backend services to TypeScript/JavaScript frontends,on a small, high-impact team.

Responsibilities

• Build customer-facing web experiences: fleet dashboards, live views/maps, alerts, admin tools, and reporting using TypeScript/JavaScript.

• Build and evolve backend services in Python that power fleet operations, integrations, data ingestion, and analytics.

• Design and implement reliable APIs (REST and/or gRPC) that are well-documented and easy to integrate with customer systems.

• Deliver real-time features (live vehicle state, events, notifications, operator workflows) using WebSockets and event-driven patterns.

• Support “physical AI” workflows by connecting cloud software to autonomy/robotics systems,telemetry pipelines, command-and-control surfaces, and operational tooling that interacts with vehicles in the real world.

• Use modern AI tools and agents to move faster and raise quality (and help build customer-facing copilot experiences where it makes sense).

• Contribute to digital-twin simulation + validation loops (where applicable): support workflows that use simulation to test behaviors, validate releases, and reproduce field issues.

• Raise engineering quality through testing, code reviews, observability, and pragmatic reliability/performance improvements.

• Own meaningful chunks of the product: shape solutions, make tradeoffs, and drive work to completion.

Qualifications

• 2–4+ years of professional software engineering experience.

• Strong production experience with:

  • Python (backend services, APIs, data workflows)

  • TypeScript or JavaScript (frontend)

  • You’ve shipped and supported user-facing web applications (not just internal tools).

  • You’re comfortable building APIs and working with databases (SQL preferred; NoSQL is a plus).

  • You communicate clearly, take ownership, and bring a low-ego, collaborative approach.

  • You care about software that’s reliable in production, not just “works locally.”

Bonus Qualifications

• Real-time systems experience: WebSockets, SSE, streaming updates, pub/sub.

• Event-driven systems / messaging: Kafka, RabbitMQ, Pulsar, etc.

• Experience with telemetry-heavy or operational products: IoT, robotics, autonomy, fleet/dispatch, industrial software.

• Experience building analytics features: reporting, aggregations, operational metrics, customer-facing insights.

• Familiarity with scaling patterns: caching, background jobs, rate limiting, performance tuning.

• Strong habits using AI coding assistants/agents responsibly (verification, testing, high-signal reviews).

• Exposure to physical AI simulation tooling (e.g., NVIDIA Omniverse / Isaac Sim) or similar environments.

Benefits & Perks

• Health benefits (Medical, Dental, Vision, HSA and FSA (Health & Dependent Daycare), Employee Assistance Program, 1:1 Health Concierge)

• Life, Short-term and long-term disability insurance (Cyngn funds 100% of premiums)

• Company 401(k)

• Commuter Benefits

• Flexible vacation policy

• Remote or hybrid work opportunities

• Sabbatical leave opportunity after 5 years with the company

• Paid Parental Leave

• Daily lunches for in-office employees

• Monthly meal and tech allowances for remote employees

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You should have a deep understanding of generative AI, hands-on experience serving generative deep learning models in production settings, and a track record of working directly with customers, iterating on solutions, and providing tailored support. Proficiency in Python and intuitive understanding of API integrations are also essential. Excellent communication skills, honed through collaborating with non-technical stakeholders, are necessary to adapt your message depending on who's in the room.

Prior experience finetuning diffusion models, working with customization tools like ComfyUI, and contributing to open-source projects in the diffusion model space are highly valued. Deploying models on cloud platforms using state-of-the-art serving infrastructure is also desirable.

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We're building a state-of-the-art Customer Data Platform, visualizing relevant insights for businesses post-onboarding and guiding customer engagement across all touch-points. Be part of the team that's redefining the way businesses connect with their customers!

Responsibilities:

• Design, implement, and maintain backend services and APIs to support applications.
• Build and optimize data storage solutions using Postgres, ClickHouse, and Elasticsearch to ensure high performance and scalability.
• Collaborate with cross-functional teams, including frontend engineers, data scientists, and machine learning engineers, to deliver end-to-end solutions.
• Monitor and troubleshoot performance issues in distributed systems and databases.
• Write clean, maintainable, and efficient code following best practices for backend development.
• Participate in code reviews, testing, and continuous integration efforts.
• Ensure security, scalability, and reliability of backend services.
• Analyze and improve system architecture, focusing on performance bottlenecks, scaling, and security.

Qualifications We Value:

• Proven experience as a Backend Engineer with a focus on database design and system architecture.
• Strong expertise in ClickHouse or similar columnar databases for managing large-scale, real-time analytical queries.
• Hands-on experience with Elasticsearch for indexing and searching large datasets.
• Proficient in backend programming languages such as Python, Go.
• Experience with RESTful API design and development.
• Solid understanding of distributed systems, microservices architecture, and cloud infrastructure.
• Experience with performance tuning, data modeling, and query optimization.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.

Perks & Benefits:

• Paid parental leave to support you and your family
• Monthly Health & Wellness allowance
• Work from home office stipend to help you succeed in a remote environment
• Lunch reimbursement for in-office employees
• PTO: 28 days in Germany

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What You'll Work On:

• Scalable data loaders for training runs across thousands of GPUs
• Efficient storage and retrieval systems for petabyte-scale datasets
• Multi-cloud object storage abstraction
• Execute large-scale data migrations across storage systems and providers
• Debug and resolve performance bottlenecks in distributed data loading

Technical Focus:

• Python, PyTorch DataLoader internals
• Object storage (e.g. S3, Azure Blob, GCS)
• Parquet for metadata
• Video: ffmpeg, PyAV, codec fundamentals

What We're Looking For:

• Built and operated data pipelines at petabyte scale
• Optimized data loading
• Worked with petabyte-scale video and image datasets
• Written processing jobs operating on millions of files
• Debugged distributed system bottlenecks across large fleets of machines

Nice to Have:

• Experience streaming dataset formats (e.g. WebDataset)
• Video codec internals and frame-accurate seeking
• Distributed systems experience
• Slurm and Kubernetes for job orchestration
• Experience with object storage performance tuning across providers

How We Work Together:

• We're a distributed team with real offices that people actually use. Depending on your role, you'll either join us in Freiburg or SF at least 2 days a week (or one full week every other week), or work remotely with a monthly in-person week to stay connected. We'll cover reasonable travel costs to make this possible. We think in-person time matters, and we've structured things to make it accessible to all. We'll discuss what this will look like for the role during our interview process.

Everything we do is grounded in four values:

• Obsessed. We are a frontier research lab. The science has to be right, the understanding deep, the product beautiful.
• Low Ego. The work speaks. The best idea wins, no matter who said it. Credit is shared. Nobody is above any task.
• Bold. We take the ambitious bet. We ship, we do not wait for conditions to be perfect.
• Kind. People over politics. We treat each other with genuine warmth. Agency without empathy creates chaos.

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Your primary focus will be on improving our video presence, creating world-class developer documentation, writing tutorials, and engaging directly with the developer community. You will work closely with our research team to shape how developers discover and learn about FLUX.

In this role, you will have the opportunity to build our local presence in the SF developer community and grow our reach online. You will be responsible for running hackathons, creating video tutorials, and maintaining open-source demo repositories.

We are looking for someone with 3+ years of experience in developer relations or a technical role with a public-facing component. You should have a proven track record of technical content creation, up-to-date engineering skills, and working knowledge of AI/ML development.

Nice to have: experience with Generative Media, finetuning/LORA of FLUX/Diffusion models.

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As a Senior Software Engineer, you'll work on high-impact systems problems such as:

• Optimizing metadata management, caching, and replication across thousands of nodes.
• Designing concurrent, fault-tolerant services for multi-region and multi-cloud environments.
• Evolving Alluxio's storage abstraction and scheduling layer to support large-scale AI/ML data pipelines.
• Collaborating with internal product teams to push the limits of distributed I/O performance.

This is a hands-on, architecture-plus-implementation role for engineers who love deep systems work and want visible impact in a small, senior, highly technical team.

What You'll Own

• Cache and metadata enhancements - design and implement improvements to caching policies, eviction logic, and metadata scalability to increase performance and reliability.
• Data path optimization - refine I/O pipelines for S3/GCS/HDFS/Posix to reduce latency and improve throughput using concurrency and scheduling techniques.
• Distributed systems reliability - strengthen consistency, replication, and fault-tolerance mechanisms across large-scale clusters.
• Feature development and integration - collaborate with product and solution-engineering teams to deliver features that support AI and analytics workloads.
• Code quality and peer collaboration - participate in design reviews, provide constructive feedback, and ensure robust testing and observability in production systems.

What We're Looking For

• Strong computer-science fundamentals and a passion for large-scale distributed systems.
• Professional experience developing in Java, C++, or Go.
• Practical knowledge of concurrency, replication, distributed coordination, and performance tuning.
• Experience with distributed storage, caching, or data-access layers (e.g., Spark, Presto, Hadoop, Kubernetes).
• Bachelor's or advanced degree in Computer Science or related technical field (or equivalent experience).

Why Alluxio?

• Build infrastructure trusted by the world's largest AI and data-driven companies.
• Join a small, senior engineering team where your designs shape the product's evolution.
• Work directly with the original creators of open-source Alluxio.
• A culture of empathy, curiosity, and ownership - where engineers collaborate closely to solve hard problems.

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As a R&D Staff Engineer, you will research, design, and implement algorithms for 3D geometry processing and mesh generation incorporating AI/ML to increase automation and robustness.

Your expertise in AI/ML applications for 3D geometry processing, proficient software development skills, especially with Python and C/C++, and solid understanding of geometry processing, mesh generation, and numerical methods are essential.

You will collaborate closely with the meshing software development team to plan, create, and evolve simulation software capabilities.

Your strong analytical skills and ability to overcome obstacles make you a natural fit for an innovative team by pushing the boundaries of simulation technology.

You will accelerate the adoption of AI/ML technologies within simulation software, making model creation faster and more accessible.

You will enable engineers and researchers to solve complex geometric and numerical problems more efficiently.

You will improve the accuracy and performance of simulation models through advanced mesh generation techniques.

You will drive innovation in the field of computational geometry and simulation technology.

You will contribute to the development of robust, scalable software solutions used by leading companies worldwide.

You will help Synopsys maintain its leadership in high-performance simulation and design automation tools.

The base salary range for this role is $120,000-$180,000.

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Key responsibilities include: Providing functional and technical subject matter expertise for Metering and AMI applications Problem analysis and resolution (production support), root cause analysis, implementing vendor solutions Providing input to application life cycle management Providing oversight for the design, development, testing, and implementation of application solutions Staying abreast of emerging computer technologies Staying abreast of the business processes emerging computer technologies

Requirements include: B.S., B.A., or B.B.A degree in Computer Science, Engineering, Management Information Systems, Business, or another related field Demonstrated technical understanding of how application frameworks and other technologies can be leveraged to help meet business needs Experience with supporting Linux based systems, creating, and updating shell scripts preferred Experience with Java/J2EE, C#/.Net Good understanding of REST/SOAP Web Services Familiarity with Windows Azure and/or Amazon Web Services Experience with Oracle databases, SQL, PL/SQL, and query performance tuning for large datasets Knowledge of business functions and operations performed within organizations of the Southern Company supported by this team (Metering and AMI) Understands and is knowledgeable of technology solutions that could impact business partners. Proven analytical skills, problem solving skills and project management skills Experience supporting vendor applications highly preferred Possess a solid understanding of technical environments and software methods Power Delivery/Customer service experience either directly or in a support role desired

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Key responsibilities include:

• Post-training/instruction tuning state-of-the-art language models, focusing on text-to-text, image/video/audio-to-text modalities and agentic capabilities
• Exploring data, reasoning, and algorithmic solutions to ensure Gemini models are safe and work for everyone
• Improving Gemini's adversarial robustness, with a focus on high-stakes abuse risks
• Designing and maintaining high-quality evaluation protocols to assess model behaviour gaps and headroom related to safety and fairness
• Developing and executing experimental plans to address known gaps or construct entirely new capabilities

To succeed in this role, you should have a PhD in Computer Science or a related field, significant LLM post-training experience, and a track record of publications at top conferences. Experience in reward modelling and reinforcement learning for LLMs instruction tuning, long-range reinforcement learning, safety, fairness, and alignment is an advantage.

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Privy is a developer tooling company that empowers users to take control of their online presence. We're looking for an experienced Engineering Manager to lead and grow a team of Infrastructure engineers.

Responsibilities

• Lead and grow a high-performing team of Infrastructure engineers
• Drive the future vision of infrastructure alongside talented infrastructure engineers
• Hold the team accountable to excellence in quality, throughput, and performance
• Ensure the team is working on the right scope of work and projects, align decisions with business impact
• Fill gaps as a player-coach; review PRs, write and review design docs, investigate incidents
• Coach engineers towards growth and their career goals

Benefits

• Competitive salary and benefits package
• Opportunity to work with a talented team of engineers
• Collaborative and dynamic work environment

Requirements

• Deep ownership and a high-level perspective on driving overall business impact
• Performance-oriented mindset, with a high bar for quality and excellence
• Technical excellence to be able to independently evaluate quality and technical feedback
• High emotional maturity, insightfulness, and care
• Strong past experience as a manager and leader

Preferred Qualifications

• Experience with designing and operating systems supporting hundreds of millions of users
• Secure enclave platforms, like AWS Nitro Enclaves
• Observability, incident response, capacity planning, performance tuning, and infrastructure automation (IaC, CI/CD for infra)
• Background in building low-latency, high-throughput systems for trading or payment processing
• Any blend of public cloud/BYOC architectures

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This role requires a passion for understanding and modeling the interactions between AI and society, a strong awareness of the AI alignment and safety landscape, and a penchant for developing novel ideas, methods, interfaces, and tools.

As a Research Scientist at Google DeepMind, you will join a team working to supercharge exploration, assessment, and steering of evolving AI behaviours, with a focus on subjective and creative tasks. You will tackle the underlying research questions to improve collaborative specification of alignment objectives and assessment of adherence to desired behaviours.

Key responsibilities include generating new ideas, executing cutting-edge ideas, communicating research findings, collaborating with other researchers, and driving technical projects.

To be successful in this role, you will need a PhD degree in Computer Science, Machine Learning, or a related technical field, a strong publication record in top machine learning conferences, and demonstrated hands-on experience in developing multimodal AI models and systems.

In addition, experience with large-scale vision language models, fine-tuning and post-training LLMs using RL, and developing agentic AI solutions to complex problems would be an advantage.

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We're looking for a versatile Research Scientist to join our Gemini Safety team at Google DeepMind. As a Research Scientist, you will be responsible for applying and developing data and algorithmic cutting-edge solutions to advance the safety and fairness behavior of our latest user-facing models.

The Gemini Safety team is accountable for the safety and fairness behavior of GDM's latest Gemini models. Our team focuses on advancing the safety and fairness behavior of state-of-the-art AI models, driving the development of foundational technology adopted by numerous product areas, including Gemini App, Cloud API, and Search.

Key Responsibilities:

• Post-training/instruction tuning state-of-the-art LLMs, focusing on text-to-text, image/video/audio-to-text modalities and agentic capabilities
• Exploring data, reasoning, and algorithmic solutions to ensure Gemini Models are safe, maximally helpful, and work for everyone
• Improve Gemini's adversarial robustness, with a focus on high-stakes abuse risks
• Design and maintain high-quality evaluation protocols to assess model behavior gaps and headroom related to safety and fairness
• Develop and execute experimental plans to address known gaps, or construct entirely new capabilities
• Drive innovation and enhance understanding of Supervised Fine Tuning and Reinforcement Learning fine-tuning at scale

About You:

• PhD in Computer Science, a related field, or equivalent practical experience
• Significant LLM post-training experience
• Experience in Reward modeling and Reinforcement Learning for LLMs Instruction tuning
• Experience with Long-range Reinforcement learning
• Experience in areas such as Safety, Fairness, and Alignment
• Track record of publications at NeurIPS, ICLR, ICML, RL/DL, EMNLP, AAAI, UAI
• Experience taking research from concept to product
• Experience with collaborating or leading an applied research project
• Experience with JAX

At Google DeepMind, we value diversity of experience, knowledge, backgrounds, and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

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This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google & top Google customers.

You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest generation models.

We are looking for a manager with a strong track record of building and shipping software, and leading engineering teams, ideally with some experience in early-stage environments, where you may have contributed to scaling products from initial concept to production.

The ideal candidate will be motivated by the opportunity to drive product & business impact, and develop strong relationships with research teams.

Responsibilities:

• Lead a team in the design and development of scalable software applications leveraging generative AI models.
• Guide the team in rapidly developing new features and iterating based on evaluation results.
• Collaborate with researchers and product managers to translate research advancements into tangible product features.
• Oversee the optimization of software performance and ensure the reliability of deployed applications.
• Champion the development of best practices for building and deploying generative AI applications.
• Lead the architecture and development of new products & features from 0 to 1.
• Mentor and develop team members, fostering a collaborative and high-performing environment.
• Partner with PM team to qualify & size new project opportunities.

Minimum qualifications:

• A bachelor degree in computer science, electrical engineering or equivalent experience.
• 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 5 years of experience in minimum of one ML field (eg. media generation, reinforcement learning, infrastructure etc.).
• 7+ years of experience leading technical projects and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning), including at least 5 years of experience in a people leadership role overseeing and guiding technical teams.

Preferred qualifications:

• Experience with generative AI models and applications.
• Contributions to open-source projects.
• Experience with front-end development.
• Proven experience in rapidly developing and shipping software products in a fast-paced, customer-facing startup-like environment, demonstrating adaptability to changing priorities.
• Experience evaluating model performance, analyzing results, and implementing improvements.
• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.

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