This high-impact role will drive the technical direction and oversight for Deep Research Agent Development, translating cutting-edge research in Generative AI, Large Language Models (LLMs), and Agentic Frameworks into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency.

The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus.

Responsibilities

Technical Leadership & Vision

• Set the Technical Roadmap: Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals.

• Drive Breakthrough Research to Production: Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities.

• Core Agent Capabilities Development:

Advanced Knowledge Retrieval: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises.

Data Analysis: Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas.

Multimodal Intelligence: Lead the integration of Multimodal AI capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent's knowledge base.

Architecture & Design: Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.

Technical Excellence: Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems.

Team Leadership & Mentorship

• Lead and Mentor: Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth.

• Recruiting & Growth: Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team.

• Cross-Functional Influence: Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent solutions.

Basic Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.

• 8+ years of experience in software development, with at least 6 years focused on Machine Learning, Deep Learning, or Applied Research in a production environment.

• 2+ years of experience in a formal or informal Technical Leadership role (Team Lead, Tech Lead) with a focus on setting technical direction for a domain.

• Deep expertise in Generative AI and Large Language Models (LLMs).

• Demonstrated experience designing, building, and deploying AI Agents or complex Agentic systems in production at scale.

• Experience with large-scale distributed systems and real-time data processing.

Preferred Qualifications

• Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field.

• Demonstrated experience designing and deploying production-grade Text-to-SQL systems, including handling complex schema linking and query optimization.

• Practical experience with Multimodal AI, specifically integrating OCR and vision-language models for document intelligence and structured data extraction from images/forms.

• Proven experience in one or more relevant deep research areas: Reinforcement Learning (RL), Reasoning and Planning, Agentic Systems.

• Experience with vector databases and advanced retrieval techniques.

• A track record of publishing research papers in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR, KDD).

• Excellent written and verbal communication skills, with the ability to articulate complex technical vision to executive stakeholders and technical peers.

• Experience driving cross-team technical initiatives that have delivered significant business impact.

Compensation

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.

About Us

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

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Your mission is threefold:

• Frontier Research & Publication: Leading research into LLM/agent capabilities, reasoning, and safety, with the goal of publishing at top-tier venues (NeurIPS, ICML, ICLR).
• Cross-Org Impact: Developing generalised techniques in Agent design, AI Safety and Deep Research agents that scale across our commercial and government platforms.
• Mission-Critical Applications: Engineering high-stakes AI systems that impact millions of citizens globally.

You will:

• Pioneer Novel Architectures: Design and train state-of-the-art models and agents, moving beyond “off-the-shelf” solutions to create custom architectures for complex public sector reasoning tasks.
• Lead AI Safety Initiatives: Research and implement robust safety frameworks, including red teaming, alignment (RLHF/DPO), and bias mitigation strategies essential for sovereign AI.
• Drive Deep Research Capabilities: Develop agents capable of long-horizon reasoning and autonomous information synthesis to solve complex problems for national security and public policy.
• Publish and Contribute: Represent Scale in the broader research community by publishing high-impact papers and contributing to open-source breakthroughs.
• Consult as a Subject Matter Expert: Act as a technical authority for public sector leaders, advising on the theoretical limits and safety requirements of emerging AI.
• Build Evaluation Frontiers: Create new benchmarks and evaluation protocols that define what success looks like for high-stakes, non-commercial AI applications.

Ideally, you’d have:

• Advanced Degree: PhD or Master’s in Computer Science, Mathematics, or a related field with a focus on Deep Learning.
• Research Track Record: A portfolio of first-author publications at major conferences (NeurIPS, ICML, CVPR, EMNLP, etc.).
• Engineering Rigour: Strong proficiency in Python, deep learning frameworks (PyTorch/JAX), with the ability to write production-ready code that scales.
• Safety Expertise: Experience in alignment, robustness, or interpretability research.

Nice to haves:

• Experience with large-scale distributed training on massive clusters.
• Experience in building agentic systems that are reliable.
• Experience in Sovereign AI or working with highly regulated data environments.
• A zero-to-one mindset: Comfortable navigating ambiguity and defining research directions from scratch.

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Key responsibilities include creating and driving engineering agendas to advance multimodal capabilities, improving data quality through annotation, filtering, augmentation, synthetic generation, captioning, and in-depth data studies, designing evaluation frameworks, metrics, benchmarks, evals, and reward models tailored to image/video/audio quality and coherence, implementing efficient algorithms for state-of-the-art model performance, and developing scalable data collection and processing pipelines for multimodal (primarily image/video-focused) datasets.

The ideal candidate will have a track record in leading studies that significantly improve neural network capabilities and performance through better data or modeling, experience in data-driven experiment designs, systematic analysis, and iterative model debugging, experience developing or working with large-scale distributed machine learning systems, and ability to deliver optimal end-to-end user experiences.

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This is a deeply product-driven role. Success is measured by real customer impact , better expense documentation, stronger policy compliance, and less time spent navigating Brex , not by novelty or research output.

Responsibilities:

• Lead and grow a team of engineers building the end-to-end conversational experience for the Brex Assistant, including outbound system-initiated interactions and inbound chat.

• Operate at all levels, guiding your team through complex technical challenges while being hands on with code and contributing to design.

• Own delivery and outcomes for the Assistant roadmap, making and executing hard sequencing decisions for agent capabilities (e.g., memory, preferences, merchant data).

• Set and uphold a high bar for reliability, correctness, and UX in non-deterministic, agentic systems operating in real-world financial workflows.

• Partner closely with Product, Design, and adjacent engineering teams (Spend, Expense, Platform) to shape direction and integrate deeply with core Brex workflows.

• Establish strong team norms and execution standards, balancing velocity with validation, quality control, and operational excellence.

Requirements:

• Proven experience leading engineering teams building user-facing products in complex, real-world domains.

• Strong product judgment, with a track record of making hard tradeoffs and delivering outcomes under real constraints.

• Experience building and operating systems that must remain reliable despite messy inputs, ambiguity, or non-deterministic behavior.

• Ability to translate high-level product goals into clear technical direction and execution plans, while mentoring engineers through strong technical and product guidance.

Bonus points:

• Development experience with Typescript while leading consumer-facing AI products, especially in regulated or high-stakes domains (finance, healthcare, travel).

• Direct experience with conversational UX, agents, or other non-deterministic systems in production.

• Prior experience as a tech lead for agentic systems, particularly in spend or financial workflows.

• Personal empathy for spend-heavy workflows (frequent travel, recruiting, managing expenses on behalf of a company).

Compensation: The expected salary range for this role is $240,000 - $300,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity.

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Your primary responsibility will be to lead conversation design and strategy for a multi-agent AI powered Pinterest Business Assistant to help business users (merchants, advertisers, and agencies) create inspired content, connect with customers, and achieve their business goals.

To succeed in this role, you'll need to act as the voice of the user by becoming an expert in our business products and leveraging research to inform the design of the AI assistant. You'll also drive improvements in prompt and skill management, owning the process from conception to production, and rapidly adapting to new technologies.

In addition to your technical skills, you'll need to be able to collaborate cross-functionally with researchers, product managers, engineers, and stakeholders to establish conversational, cohesive experiences with a unified voice. You'll apply systematic thinking to your work, contributing to scalable, consistent design patterns, and participating in critique to strengthen your designs.

As a Sr. Staff GenAI Content & Conversational Designer, you'll actively seek learning opportunities to grow your craft, define success metrics for novel AI features, and obsess over building trustworthy, high-impact AI systems.

We're looking for someone with a strong background in user-focused product conversation and content design, with experience shaping content for multi-disciplinary projects. You should have experience with LLMs, prompt shaping/engineering and working on AI product flows and with agentic systems. A portfolio demonstrating breadth and creativity and proven experience in content design, design thinking and product strategy is essential.

This position is not eligible for relocation assistance. You'll need to be in the office for in-person collaboration 1-2 times/quarter, and therefore can be situated anywhere in the country.

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You will be accountable for both people leadership and product outcomes, guiding how agentic systems are designed, shipped, and operated in production. This is a deeply product-driven role. Success is measured by real customer impact , better expense documentation, stronger policy compliance, and less time spent navigating Brex , not by novelty or research output.

The role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday.

Responsibilities:

• Lead and grow a team of engineers building the end-to-end conversational experience for the Brex Assistant, including outbound system-initiated interactions and inbound chat.

• Operate at all levels, guiding your team through complex technical challenges while being hands on with code and contributing to design.

• Own delivery and outcomes for the Assistant roadmap, making and executing hard sequencing decisions for agent capabilities (e.g., memory, preferences, merchant data).

• Set and uphold a high bar for reliability, correctness, and UX in non-deterministic, agentic systems operating in real-world financial workflows.

• Partner closely with Product, Design, and adjacent engineering teams (Spend, Expense, Platform) to shape direction and integrate deeply with core Brex workflows.

• Establish strong team norms and execution standards, balancing velocity with validation, quality control, and operational excellence.

Requirements:

• Proven experience leading engineering teams building user-facing products in complex, real-world domains.

• Strong product judgment, with a track record of making hard tradeoffs and delivering outcomes under real constraints.

• Experience building and operating systems that must remain reliable despite messy inputs, ambiguity, or non-deterministic behavior.

• Ability to translate high-level product goals into clear technical direction and execution plans, while mentoring engineers through strong technical and product guidance.

Bonus points:

• Development experience with Typescript while leading consumer-facing AI products, especially in regulated or high-stakes domains (finance, healthcare, travel).

• Direct experience with conversational UX, agents, or other non-deterministic systems in production.

• Prior experience as a tech lead for agentic systems, particularly in spend or financial workflows.

• Personal empathy for spend-heavy workflows (frequent travel, recruiting, managing expenses on behalf of a company).

Compensation: The expected salary range for this role is $240,000 - $300,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

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Anthropic is looking for experienced, product-minded engineers to own the backend systems that power user experiences across our API, Claude Code, and Claude.ai.

You'll independently scope complex, multi-month projects through ambiguous problem spaces and lead peers through technical and product decisions; you'll drive alignment with product, peer engineering teams, and research to identify capability gaps and translate frontier model improvements into shipped products.

You'll make architectural decisions that affect the reliability and scalability of systems serving hundreds of thousands of global users (including internal teams), and design processes that help your team operate effectively and never fail the same way twice - all while staying hands-on with the code and our models.

Teams

We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organisational needs.

• API Core: You'll build and scale the foundation of the Claude API,the systems that deliver Claude's intelligence to every developer, from startups to enterprise.
• API Capabilities: You'll bring frontier model capabilities to developers through the Claude API, owning core features like vision, tool use, and computer use.
• API Knowledge: You'll focus on transforming Claude into a true knowledge worker by ensuring the model has access to and understanding of the right knowledge at the right time.
• Developer Experience: You’ll focus on building products and tools to enable developers to harness the full power of LLMs to create successful, reliable, and groundbreaking applications with ease.
• API Agents: You'll focus on building the infrastructure and APIs that enable developers to create powerful agentic applications within the Claude API.
• Enterprise Foundations: We're looking for a software engineer to join our Enterprise Foundations team,the team that makes Claude enterprise-ready at scale.

Requirements

• Have 8+ years of relevant experience as a backend or product engineer, with a track record of leading complex, multi-month projects or teams as a tech lead or equivalent.
• Have strong coding fundamentals and are comfortable working across backend systems, APIs, and integrations , and can reach into the frontend when needed to ship an effective solution.
• Have led the design and delivery of large-scale backend systems in production that power high-adoption B2B or consumer-facing products.
• Are skilled at driving alignment across technical and non-technical teams; you communicate clearly, influence technical decisions beyond your immediate team, and help others ramp effectively on your systems.
• Take a product-focused approach to your work and care about building solutions that are robust, scalable, and easy to use.
• Care deeply about investing in the mentorship and growth of your peers.
• Have experience with distributed systems, API design, and cloud infrastructure at scale.
• Thrive in fast-paced environments and can navigate ambiguity to find the highest-leverage path forward.

Preferred Qualifications

• Served as a technical lead or architect on a product or API platform, owning both the technical vision and execution end-to-end.
• Experience designing and scaling APIs with a focus on developer experience, consistency, and reliability , including API design review processes.
• Deep experience building enterprise SaaS platforms, including permissions infrastructure, billing and pricing systems, or compliance frameworks for regulated industries (SO2, HIPAA).
• Background in a specific industry vertical , financial services, healthcare, or legal technology , with a track record of building products that handle sensitive, domain-specific data.
• Experience partnering with ML/AI research teams to productize model capabilities or identify and address model failure modes in production.
• Experience building agentic systems, orchestration frameworks, or developer tools , including CLI tools, IDE integrations, or AI-assisted coding environments.
• Experience building products where adoption and activation are core challenges , instrumenting funnels, diagnosing drop-off, and shipping the product changes that close gaps.
• Experience designing operational processes (incident response, on-call rotations, postmortem review) for production systems serving large-scale developer or enterprise audiences.

Compensation

The annual compensation range for this role is $405,000-$485,000 USD.

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While traditional NLP focuses on analyzing static text, your work will center on real-time, multimodal systems that can listen, reason, and take action during live customer interactions.

A major focus of the team is advancing DialpadGPT, our proprietary LLM, specifically optimizing it to drive orchestrated agentic workflows and handle complex task execution.

Beyond the technical skills, we are a team that values collaboration, continuous learning, and the application of diverse perspectives to solve complex problems.

Collaboration will be key as you work alongside our engineering, design, and product teams to build groundbreaking agentic applications.

If you're passionate about agentic and multimodal AI and contributing to a team that's changing the face of business communications, you'll find yourself right at home with us.

This position reports to the Senior Manager of the NLP team and has the opportunity to be based in Vancouver, BC.

Key responsibilities include:

• Research and develop state-of-the-art algorithms for autonomous voice agents, specifically focusing on real-time speech processing and reasoning loops.

• Advance DialpadGPT: Design and execute distributed training strategies to optimize our proprietary LLMs for agentic behaviors, including precise tool use, instruction following, and latency-constrained generation.

• Conduct rigorous evaluation and monitoring of model performances and troubleshoot issues with a keen understanding of resultant business impacts.

• Design and implement orchestration layers that effectively chain LLMs with external tools and APIs to solve complex customer problems autonomously.

• Work with large-scale multimodal datasets (text, audio) to improve model robustness and alignment.

• Collaborate with engineering, product, and design teams to deploy scalable, low-latency models and algorithms in production.

• Submit papers to top-tier academic conferences (ACL, EMNLP, NeurIPS) and contribute to the team’s research culture.

To succeed in this role, you'll need:

• A Master’s or PhD degree in Computer Science, Machine Learning, Computational Linguistics, or a related quantitative field.

• 2+ years of industry experience in Machine Learning/NLP for Master’s degree holders, or 1+ years for PhD holders.

• Deep understanding of LLMs: Demonstrated experience with training, fine-tuning (PEFT/LoRA), and alignment techniques (RLHF/DPO) for specific domains or tasks.

• Experience with Agentic Systems: Familiarity with building autonomous agents, including concepts like tool use, function calling, reasoning chains (CoT), and memory management.

• Strong proficiency in Python and PyTorch, with the ability to write clean, production-ready research code.

• Research Track Record: A history of publishing in top-tier conferences (ACL, EMNLP, NeurIPS, ICASSP) is highly valued.

• Multimodal Awareness: Familiarity with speech technologies (ASR, TTS) or processing real-time audio streams is a strong plus.

• Ability to bridge the gap between research and product, translating complex technical concepts into business value.

• Familiarity with version control tools like Git for collaborative projects.

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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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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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Your 下 responsibilities will include:

• Owning the agentic tools platform, including the registry of capabilities agents can invoke, the standards for how tools are built, and the governance for how they're deployed.
• Balancing the tension between enabling rapid tool development and maintaining the reliability that production agents demand.
• Architecting integration strategy, including determining which integrations unlock disproportionate value, negotiating technical partnerships, and defining the abstraction layers that make integrations composable rather than brittle.
• Driving agentic execution excellence, including partnering with ML engineers on tool selection optimization, prompt engineering for reliable tool invocation, and error handling patterns that make agents resilient.
• Enabling internal tool development, including building the developer experience,documentation, templates, testing frameworks, deployment pipelines,that lets teams ship new tools without deep platform expertise.

In this role, you will be working at the forefront of agentic technology, evaluating innovations and determining which advances warrant immediate adoption versus patient observation. You will also be responsible for navigating the agentic frontier, including bringing external best practices to ZoomInfo while contributing learnings back to the community.

To be successful in this role, you will need to have a strong background in product management, with 6-15 years of experience in AI/ML infrastructure, developer platforms, or integration products. You should also have direct experience with production agentic systems, hands-on familiarity with agentic frameworks, and a track record of building platform products where engineering teams are your customers.

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This is a role that sits at the intersection of product thinking, service design, and cross-functional influence. You will design, manage, and enable the services that move customers forward at every stage of that journey.

Your responsibilities will include:

• Owning the end-to-end service portfolio for your assigned product area , offer design, pricing, BOM standards, lifecycle management, field enablement, and sunset decisions
• Mapping and continuously refining the complete customer journey for your product area, defining how customers are guided across scaled digital motions, Customer Success Tiers, Professional Services, and Education and Training
• Defining measurable customer outcomes and value anchors for each offering, ensuring every service can clearly articulate what success looks like and how it is verified
• Acting as product manager for your product area tooling requirements into the CX Engineering Platform team , writing requirements, reviewing prototypes, managing a backlog, and conducting UAT
• Partnering with PS Engineers, Customer Success, Project Managers, and Solution Architects to gather field input and translate it into refined or net-new service offerings
• Building and maintaining relationships with stakeholders across the full organizational range , from PSEs and CSMs who deliver your services in the field, through to VP-level PS and CS leadership and C-suite executives
• Collaborating with your peers across the CX Services Portfolio team to design consistent customer experiences and ensure services are properly sequenced across the customer lifecycle
• Creating and maintaining field enablement materials , playbooks, objection handling guides, Highspot pages, talk tracks, and training sessions , for CSMs, CSAs, PSEs, and AEs
• Using AI tools actively in your daily workflow to accelerate research, drafting, synthesis, and requirement writing , and contributing what you learn to the team shared AI practice

To succeed in this role, you will need:

• 7+ years of experience in professional services, customer success, solutions architecture, or product management at a SaaS company
• Demonstrated experience designing or managing service offerings , not just delivering them. You have written a scope of work, defined pricing, and built a delivery kit
• Strong understanding of DevOps, application development, SDLC, or security domains , you do not need GitLab product knowledge on day one, but you need the technical foundation to develop it quickly
• Technical depth sufficient to design credible services. You do not need to have delivered these engagements yourself, but you need to understand them well enough that the practitioners who do will trust your judgment
• Deep familiarity with AI/ML engineering workflows, LLM capabilities, and agentic systems , and the organizational change management required for enterprise AI adoption
• A demonstrated AI-forward working style , you actively use agentic coding and AI tools as part of your daily workflow. You have formed opinions about how these tools change the way you work, and you can walk us through a specific workflow you have built or discovered that materially changed your output quality or speed
• Proven ability to build trust and communicate effectively across the full stakeholder range , individual contributors, managers, directors, VPs, and C-suite , in a remote, async-first environment
• Commercial acumen: fluency in how professional services and subscription services are priced, packaged, and sold in an enterprise context
• Strong written communication skills: you can produce clear, concise, and compelling content that resonates with diverse audiences

If you're passionate about designing and delivering exceptional customer experiences, and you have a strong background in professional services, customer success, or product management, we encourage you to apply for this exciting opportunity.

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Key responsibilities include:

• Developing and owning the People Systems roadmap in partnership with the People and Business Technology teams
• Working with Workday HCM and integrating it with other People systems to ensure optimal configuration, security, compliance, integration, and performance
• Leading and mentoring a team, fostering a culture of innovation, accountability, and continuous improvement
• Collaborating closely with People Operations, Total Rewards, Finance, IT, and Security teams to deliver seamless workflows and data consistency across platforms
• Overseeing system implementations, enhancements, and integrations from planning through post-launch support
• Exploring and implementing agentic AI solutions to enhance workflows and streamlining decision-making
• Partnering with the People Team to prototype solutions on the Airtable platform to optimise People processes, reporting, and collaboration across teams
• Championing data accuracy, privacy, and compliance across all HR systems and enabling actionable people analytics and reporting
• Identifying opportunities to automate and streamline HR processes, improve user experience, and support strategic workforce planning

Requirements include:

• 10+ years of experience in HR technology, with at least 3 years in a leadership or people management role
• 6+ years of hands-on expertise in Workday HRIS (core HCM, Compensation, Talent, Recruiting, and/or Advanced Reporting)
• Strong understanding of HR processes and systems architecture, including integrations with other SaaS tools
• Demonstrated ability to experiment with and implement AI-driven or agentic systems, automations, or chat-based tools within business workflows
• Curious and growth mindset to build or prototype operational tools or workflows in Airtable or similar platforms
• Proven success leading system implementations, upgrades, and cross-functional projects in a fast-paced environment
• Excellent stakeholder management, communication, and change management skills
• Analytical mindset with the ability to translate data into business insights
• Familiarity with technologies such as Airtable, Greenhouse, Workramp, Glint, Gem, etc.

Preferred experience includes:

• Bachelor's degree in Information Systems, Human Resources, or related field
• Experience scaling People Systems in a global or rapidly growing organisation
• Familiarity with iPaaS tools like Workato or Boomi

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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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Responsibilities:

• Create and drive engineering agendas to advance multimodal capabilities, with emphasis on image and video generation, editing, understanding, controllable/long-horizon synthesis, agentic planning, RL training, and world simulation (including audio integration for richer video experiences).
• Improve data quality through annotation, filtering, augmentation, synthetic generation, captioning, and in-depth data studies, particularly for visual and audio data.
• Design evaluation frameworks, metrics, benchmarks, evals, and reward models tailored to image/video/audio quality and coherence.
• Implement efficient algorithms for state-of-the-art model performance, including real-time inference, distillation, and scalable serving for visual content.
• Develop scalable data collection and processing pipelines for multimodal (primarily image/video-focused) datasets.
• Collaborate cross-functionally to integrate AI solutions into production and rapidly iterate based on user feedback.

Basic Qualifications:

• Track record in leading studies that significantly improve neural network capabilities and performance through better data or modeling.
• Experience in data-driven experiment designs, systematic analysis, and iterative model debugging.
• Experience developing or working with large-scale distributed machine learning systems.
• Ability to deliver optimal end-to-end user experiences.
• Hands-on contributor with initiative, excellence, strong work ethic, prioritization skills, and excellent communication.

Preferred Skills and Experience:

• Experience in SFT, RL, evals, human/synthetic data collection, or agentic systems.
• Proficiency in Python, JAX/XLA, PyTorch, Rust/C++, Spark, Ray, and related large-scale frameworks.
• Domain expertise in multimodal applications such as graphics engines, rendering techniques, image/video understanding and generation, world models, real-time simulation, or controllable/long-horizon visual content creation (audio/speech processing or music/audio generation experience is a plus where it supports video).
• Experience with agentic RL training, controllable/long-horizon generation, or multimodal agents that reason and act across modalities (especially in visual domains).

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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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The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.

As a first Evaluation Engineer, you'll design the methodology, build the infrastructure, and define what 'ready for production' means across verticals and use cases. You will design and implement evaluation systems that help our customers understand model performance across their specific use cases, build robust evaluation infrastructure, and work closely with both research and customer-facing teams.

Research builds evals for frontier capabilities but customers don't care about MMLU scores. We need in Applied AI evals and frameworks for customer reality domain-specific, risk-aware, production-grade. The kind that tell you whether your medical summarization model will hallucinate drug interactions, or whether your legal assistant will invent case citations.

This role sits at the intersection of research, engineering, and solutions, you will play a critical cross role in measuring, understanding, and improving the capabilities of our models for our enterprise customers.

Responsibilities

• Design and implement comprehensive evaluation frameworks to measure LLM capabilities across diverse customer use cases, including text generation, reasoning, code, and domain-specific applications

• Build scalable evaluation infrastructure and pipelines that enable rapid, reproducible assessment of model performance

• Develop novel evaluation methodologies to assess emerging capabilities or verticalized use cases (cybersecurity, finance, healthcare, etc.) and enable the Solutions (Deployment Strategist and Applied AI) on these topics

• Create custom evaluation suites tailored to enterprise customers' specific needs, working closely with them to understand their requirements and success criteria

• Collaborate with research teams to translate evaluation insights into model improvements and training decisions

• Partner with product teams to continuously improve our evaluation tooling based on customer 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

• 3+ years of experience in ML evaluation, benchmarking for LLM or agentic systems

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

• 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:

• Contributions to open-source evaluation frameworks (e.g., LM Eval Harness, OpenAI Evals) or published research on LLM evaluation

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

• Experience with ML frameworks (PyTorch, HuggingFace Transformers)

Benefits

• PTO: The CDI contract will be a 'Forfait 218 jours', corresponding to 25 days of holidays and on average 8 to 10 days of RTT days, and complete autonomy on working hours

• Health: Full health insurance coverage for you and your family

• Transportation: We offer a €600 annual mobility allowance. This package covers 50% of your public transportation costs and includes the Sustainable Mobility Allowance (FMD), encouraging eco-friendly travel options such as cycling or carpooling

• Food: Swile meal vouchers with 10,83€ per worked day, incl 60% offered by company

• Sport: Gymlib - sponsorship by Mistral of a significant part of the monthly fee (depending on the program you chose)

• Parental policy: 4 additional weeks for parents on top of what is offered by the French state

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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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The AI platform for investors and bankers that generates alpha and drives upside.

Founded in 2020 by George Sivulka and backed by Peter Thiel and Andreessen Horowitz, Hebbia powers investment decisions for BlackRock, KKR, Carlyle, Centerview, and 40% of the world's largest asset managers. Our flagship product, Matrix, delivers industry-leading accuracy, speed, and transparency in AI-driven analysis. It is trusted to help manage over $30 trillion in assets globally.

We deliver the intelligence that gives finance professionals a definitive edge. Our AI uncovers signals no human could see, surfaces hidden opportunities, and accelerates decisions with unmatched speed and conviction. We do not just streamline workflows. We transform how capital is deployed, how risk is managed, and how value is created across markets.

Hebbia is not a tool. Hebbia is the competitive advantage that drives performance, alpha, and market leadership.

The Role

Engineering Managers at Hebbia are technical leaders who build, ship, and lead. Every manager on our team writes code, reviews pull requests, and makes architecture decisions alongside the engineers they lead. This role requires strong technical ability. If you are looking for a role that is purely people management, this is not the right fit.

You will own a team and a problem space. You will set technical direction, unblock engineers, raise the bar on quality, and ship product that our customers rely on to make investment decisions. You are a strong partner to your product counterpart, and when they are out you drive the product yourself. Product intuition and business understanding are as important as technical depth in this role. You will also hire, coach, and grow your team. Our interview process reflects how we work: expect systems design, coding, and architecture discussions in addition to leadership and management conversations.

Responsibilities

• Own the technical direction and delivery for your team. Set roadmap priorities, define architecture, and make tradeoffs between speed and quality.
• Write and review code. You will spend meaningful time in the codebase, not in meetings about the codebase.
• Hire, coach, and develop engineers. Run effective 1:1s, give direct feedback, and build a team that compounds in strength over time.
• Drive operational excellence for the systems your team owns: monitoring, incident response, on-call, and reliability.
• Collaborate with product and design to translate customer problems into technical solutions that ship fast. When your PM is unavailable, you own the product direction for your team.
• Work directly with customers and internal stakeholders to understand requirements and inform priorities.
• Identify and pay down technical debt. Make pragmatic decisions about when to invest in foundations versus when to move fast.
• Raise the engineering bar across the organization through better tooling, processes, and culture.

Who You Are

• 7+ years of software engineering experience at a venture-backed startup or top-tier technology company, with at least 2 years in a technical lead or engineering management role
• You still write code and want to keep writing code. You see management as a way to multiply impact, not a way to stop building.
• Strong systems design and architecture skills. You can design, critique, and evolve complex distributed systems.
• Experience building and scaling backend systems, data pipelines, or platform infrastructure in production
• Track record of hiring and developing strong engineers. You know what good looks like and you can attract it.
• Strong product intuition. You understand what customers need, why it matters to the business, and can make good product decisions independently.
• High ownership and urgency. You take accountability for outcomes, not process.
• Comfortable working in ambiguity. Priorities shift, requirements are underspecified, and you figure it out.
• Experience with cloud platforms (e.g., AWS) and modern backend technologies (Python, TypeScript, Go)
• Strong communicator. You can create clarity for your team, your stakeholders, and your customers.
• Experience building or leading teams that work with LLMs, agentic systems, or applied AI/ML in production is a plus
• Background in applied research or experience bridging research and production engineering is a plus
• Experience with enterprise customers, particularly in finance, legal, or consulting domains is a plus

Compensation

The salary range for this role is $200,000 to $300,000. This range may be inclusive of several career levels at Hebbia and will be narrowed during the interview process based on the candidate's experience and qualifications. Adjustments outside of this range may be considered for candidates whose qualifications significantly differ from those outlined in the job description.

Life @ Hebbia

• PTO: Unlimited
• Insurance: Medical + Dental + Vision + 401K
• Eats: Catered lunch daily + DoorDash dinner credit if you ever need to stay late
• Parental leave: 3 months non-birthing parent, 4 months for birthing parent
• Fertility benefits: $15k lifetime benefit
• New hire equity grant: Competitive equity package with unmatched upside potential

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About the Role:

As an Applied Research Engineer, you will be the bridge between research, industry, and application shaping the future of our core natural language processing systems. You will be responsible for enabling agentic capabilities across the Hebbia product suite. You will own experiments and POCs focused on combining the latest research findings with specific high-value problems that our customers encounter each and every day.

Responsibilities:

• Focused on LLMs, you will play a crucial role in analyzing and interpreting complex data types to derive and implement cutting-edge insight generation systems.
• Iterate and explore new LLM and NLP techniques maintaining our foothold as an industry leader.
• You will utilize your expertise in statistics, programming, and machine learning to develop and deploy data-driven models and algorithms.
• Your work will contribute to solving business problems, improving processes, and enhancing the overall performance of the company.
• Collaborate with cross-functional teams to improve NLP/LLM capabilities in app.
• Stay up-to-date with the latest advancements and research in the space.
• Collaborate with software engineers to integrate agentic capabilities into existing systems or develop new applications.
• Ensure that systems are efficient, maintainable, and well-monitored.
• Iterate on validation and testing frameworks.

Requirements:

• Bachelor's degree in Computer Science, Engineering, or related field.
• Master's degree in Computer Science, Mathematics, Machine Learning, or a related field is a plus.
• 7+ years software development experience at a venture-backed startup or top technology firm, with a focus on applied machine learning systems.
• Strong programming skills in Python.
• Experience with NLP and text processing libraries such as NLTK, SpaCy, or Apache Tika.
• Experience with Search and Indexing technologies.
• Proficient in machine learning techniques and algorithms.
• Experience working with foundational models and corresponding APIs.
• Knowledge of statistical analysis and data scraping techniques.
• Prior experience in developing NLP models and systems.
• Experience with prompting and building LLM applications and agents is a plus.

Benefits:

• Experience building agentic systems or LLM-enabled products.
• Frequent user of AI products, especially during the development lifecycle (i.e., Cursor, Claude Code, etc).

Compensation:

The salary range for this role is $160,000 to $300,000. This range may be inclusive of several career levels at Hebbia and will be narrowed during the interview process based on the candidate's experience and qualifications. Adjustments outside of this range may be considered for candidates whose qualifications significantly differ from those outlined in the job description.

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You'll work across systems like Snowflake, S3, SharePoint, and internal customer infrastructure , building pipelines that need to handle real-world complexity: unreliable APIs, evolving schemas, massive datasets, and edge cases that don’t show up in documentation.

This role is hands-on, high-ownership, and deeply technical. You won’t just write code , you’ll develop the instincts to operate and debug complex distributed systems in production.

You will build connectors and ingestion pipelines that bring enterprise data into Hebbia's AI platform, from Snowflake warehouses and SharePoint libraries to live pricing feeds, high-velocity news data, and proprietary customer systems.

You will design and operate pipelines that handle scale, failures, and edge cases gracefully.

You will debug issues across APIs, auth systems, and data formats, often under real-time customer pressure.

You will own reliability end-to-end: monitoring, alerting, on-call, and incident response.

You will improve internal tooling and observability to make systems more robust and easier to operate.

You will partner with product and customer teams to scope, prioritize, and ship the integrations that unlock Hebbia's highest-value use cases.

You will design and ship agents that sit on top of the ingestion layer, making enterprise data accessible and actionable across all of Hebbia's product surfaces , from document analysis to structured query workflows.

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• Own critical system components: Take complex requirements and turn them into robust, scaled solutions that solve real customer needs.
• Unlock O(1) universal indexing: Build and iterate on our high-scale document build system that enables constant time latency for indexing any content in the world, regardless of data volume.
• Drive performance optimization: Architect and implement performance-tuning solutions to ensure our systems operate efficiently at scale, minimizing latency and maximizing throughput across millions of documents.
• Mentor and guide: Provide technical leadership, mentorship, and guidance to junior engineers, fostering a culture of learning and growth.

To succeed in this role, you will need:

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• 5+ years software development experience at a venture-backed startup or top technology firm, with a focus on backend software engineering.
• Proficiency in building backend and API systems using technologies such as Python, Java, or Go.
• Extensive experience with cloud platforms (e.g., AWS).
• Working experience with one or more of the following: Kafka, ElasticSearch, PostgreSQL, and/or Redis.
• Ability to analyze complex problems, propose innovative solutions, and effectively communicate technical concepts to both technical and non-technical stakeholders.
• Proven experience in leading software development projects and collaborating with cross-functional teams.
• Strong interpersonal and communication skills to foster a collaborative and inclusive work environment.
• Enthusiasm for continuous learning and professional growth. A passion for exploring new technologies, frameworks, and software development methodologies.
• Embraces rapid prototyping with an emphasis on user feedback.
• Autonomous and excited about taking ownership over major initiatives.

As a bonus, experience building agentic systems or LLM-enabled products, frequent use of AI products, especially during the development lifecycle, will be highly valued.

The salary range for this role is $160,000 to $300,000. This range may be inclusive of several career levels at Hebbia and will be narrowed during the interview process based on the candidate's experience and qualifications.

At Hebbia, we offer a range of benefits, including:

• Unlimited PTO
• Medical, dental, and vision insurance
• 401K plan
• Catered lunch daily
• DoorDash dinner credit if you ever need to stay late
• 3 months non-birthing parent leave, 4 months for birthing parent
• $15k lifetime fertility benefit
• Competitive equity package with unmatched upside potential

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At Eve, we're redefining what's possible in legal technology. Our mission is to empower plaintiff law firms with AI-driven solutions that elevate how they operate, serve clients, and grow.

We're looking for a seasoned architect to shape Eve's core platform, from infrastructure and reliability to AI-powered experiences used daily by hundreds of law firms. As a key member of our team, you will:

• Architect the future of Eve's core platform, delivering high-quality releases, driving increased value, and ensuring reliability, availability, and scalability for our growing customer base.

• Drive product and technical strategy, partnering with Product, Design, and Engineering teams to turn ambitious ideas into scalable, customer-loved products.

• Hire and develop world-class talent, recruiting, mentoring, and growing exceptional engineers and managers. Foster a culture where speed and quality coexist.

• Scale engineering at startup speed, leading multiple high-performing teams building Eve's most critical systems.

• Raise the bar for excellence, building the systems, frameworks, and culture that enable a fast-growing organization to ship with precision and confidence.

What We Are Looking For

• Proven track record in a high-growth startup or similar environment, plus the ability to dive in and be hands-on if necessary.

• Deep technical expertise in system design, reliability, or large-scale product engineering.

• Bonus: Agentic systems or more AI-native product building experience.

• Builder mindset: comfortable diving into technical details when needed, but focused on creating leverage and clarity for others.

• A leader who knows when to coach, intervene, or move out of the way, enabling engineers to operate with ownership and pride.

• Strong product and business intuition: you care as much about what we build as how we build it.

• Passion for AI-driven products and a desire to help shape how this technology transforms an entire industry.

Benefits

• Competitive Salary & Equity

• 401(k) Program with Employer Matching

• Health, Dental, Vision and Life Insurance

• Short Term and Long Term Disability

• Commuter Benefits

• Autonomous Work Environment

• Office Setup Reimbursement

• Flexible Time Off (FTO) + Holidays

• Quarterly Team Gatherings

• In-office Perks

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Responsibilities:

• Building and iterating on fee explainability experiences that empower users to find answers independently
• Developing agentic systems with strong accuracy guarantees,building evaluation frameworks and ensuring reliability at scale
• Creating performant data aggregations and optimizations to handle complex pricing scenarios
• Working across the stack: backend services, frontend experiences, data pipelines, and AI agents
• Collaborating with stakeholders across engineering, product, operations, finance, accounting, and sales
• Independently identifying solutions to user pain points and executing against roadmaps
• Mentoring junior engineers and raising the technical bar for the team

Requirements:

• 5+ years of professional experience in a software development role
• Strong coding skills in any programming language
• Ability to drive and lead large-scale initiatives that solve critical business challenges
• Strong collaboration skills across teams and workstreams
• Track record of developing and delivering high-quality software using industry best practices
• Ability to make effective tradeoffs that balance business priorities, user experience, and technical sustainability

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About Us

DeepMind's RL team is a long-standing and tight-knit team of collaborative scientists and engineers, led by Tom Schaul. We tackle large scale research challenges in reinforcement learning. We design, refine, and scale RL algorithms and deliver meaningful scientific or product impact. Over the past decade, members of the RL team have been instrumental in building DQN, AlphaGo, Rainbow, AlphaZero, MuZero, AlphaStar, AlphaProof and Gemini.

The Role

As a Research Scientist, you'll use machine learning knowledge and technical know-how to innovate, drive research projects, as well as apply research to impactful problems. You will be expected to implement code, run experiments, own results end-to-end, communicate them internally or externally, as well as collaborate with and empower others.

Your work may involve:

• Initiating or pursuing novel research directions, by proposing and testing research hypotheses.
• Implementing algorithm ideas and run end-to-end experiments, including setup, execution, analysis, and iteration.
• Sharing your skills and knowledge with other researchers.
• Building or improving infrastructure for research at scale.
• Designing evaluations and ablations that answer real questions and change minds.
• Analyzing results carefully, including debugging and failure analysis.
• Communicating clearly through plots, writeups, and paper-ready narratives and figures.
• Contributing to a culture of first-principles thinking, high standards, and direct, constructive feedback.

Our projects span the full range of state-of-the-art machine learning and AI fields, including large language models, distributed machine learning techniques, and much more, but with an emphasis on reinforcement learning.

We take a holistic view of people's backgrounds, and do not expect you to be an expert in all areas. We do expect you to proactively and quickly adopt new technologies and systems, but we also invest a lot of time in training and helping people to continually learn as part of their role.

About You

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

• A passion for reinforcement learning
• A research track record in RL, including peer-reviewed publications.
• Strong implementation ability and comfort working in research codebases.
• Evidence of owning experiments end-to-end, including analysis and interpretation.
• Strong communication skills and a bias toward clarity and honesty regarding results.
• High agency and drive: You push projects forward, prioritize effectively, and take initiative.
• PhD in ML preferred, or equivalent practical experience.

In addition, the following would be an advantage:

• Experience with RL for sequence models, post-training, preference-based learning, or agentic systems.
• Experience with modern research stacks (e.g., JAX/Flax or PyTorch) and scaling experiments.
• Strong experimental taste: Good judgment regarding baselines, ablations, and what is worth testing.
• Comfort with scaling, evaluation methodologies, and diagnosing complex failure modes.
• A focus on craft: You care about doing excellent work while maintaining a high velocity.

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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 global organisation with teams distributed between France, USA, UK, Germany, and Singapore. Our comprehensive AI platform meets enterprise needs, whether on-premises or in cloud environments.

Our offerings include le Chat, the AI assistant for life and work.

About The Job

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.

As a first Evaluation Engineer, you'll design the methodology, build the infrastructure, and define what 'ready for production' means across verticals and use cases. You will design and implement evaluation systems that help our customers understand model performance across their specific use cases, build robust evaluation infrastructure, and work closely with both research and customer-facing teams.

Research builds evals for frontier capabilities but customers don't care about MMLU scores. We need in Applied AI evals and frameworks for customer reality domain-specific, risk-aware, production-grade. The kind that tell you whether your medical summarization model will hallucinate drug interactions, or whether your legal assistant will invent case citations.

This role sits at the intersection of research, engineering, and solutions, you will play a critical cross role in measuring, understanding, and improving the capabilities of our models for our enterprise customers.

Responsibilities

• Design and implement comprehensive evaluation frameworks to measure LLM capabilities across diverse customer use cases, including text generation, reasoning, code, and domain-specific applications

• Build scalable evaluation infrastructure and pipelines that enable rapid, reproducible assessment of model performance

• Develop novel evaluation methodologies to assess emerging capabilities or verticalized use cases (cybersecurity, finance, healthcare, etc.) and enable the Solutions (Deployment Strategist and Applied AI) on these topics

• Create custom evaluation suites tailored to enterprise customers' specific needs, working closely with them to understand their requirements and success criteria

• Collaborate with research teams to translate evaluation insights into model improvements and training decisions

• Partner with product teams to continuously improve our evaluation tooling based on customer 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

• 3+ years of experience in ML evaluation, benchmarking for LLM or agentic systems

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

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

• You have strong technical coding skills in Python

Ideally You Have:

• Contributions to open-source evaluation frameworks (e.g., LM Eval Harness, OpenAI Evals) or published research on LLM evaluation

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

• Experience with ML frameworks (PyTorch, HuggingFace Transformers)

Benefits

PTO: The CDI contract will be a 'Forfait 218 jours', corresponding to 25 days of holidays and on average 8 to 10 days of RTT days, and complete autonomy on working hours

Health: Full health insurance coverage for you and your family

Transportation: We offer a €600 annual mobility allowance. This package covers 50% of your public transportation costs and includes the Sustainable Mobility Allowance (FMD), encouraging eco-friendly travel options such as cycling or carpooling

Food: Swile meal vouchers with 10,83€ per worked day, incl 60% offered by company

Sport: Gymlib - sponsorship by Mistral of a significant part of the monthly fee (depending on the program you chose)

Parental policy: 4 additional weeks for parents on top of what is offered by the French state

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We're looking for research engineers with a strong computer vision background who believe that visual and spatial reasoning are core to fully unlocking the capabilities of LLMs. In this role, you'll work on research, development, and evaluation for state-of-the-art Claude models, with a focus on visual and spatial capabilities.

What you'll do:

• Run experiments to evaluate architectural variants, data strategies, and SL and RL techniques to improve Claude's vision

• Develop and test tools, skills, and agentic infrastructure that enable Claude to reason over visual inputs

• Create evaluations and benchmarks that measure progress on multimodal capabilities across training and deployment

• Work with our product org to find solutions to our most vexing API customer challenges related to vision and spatial reasoning

You may be a good fit if you:

• Have 7+ years of ML, computer vision, and software engineering experience through industry, academia, or other projects

• Are familiar with the architecture, training, and operation of large vision language models

• Have experience creating and evaluating large synthetic and real-world visual training datasets

• Have experience engaging in systematic prompting, finetuning, or evaluation

• Are results-oriented, with a bias towards flexibility and impact

• Enjoy pair programming and cross-team collaboration

• Care about the societal impacts of your work

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)

• Large-scale ETL and data pipeline development

Representative projects:

• Running experiments to determine ideal training datamixes and parameters for a synthetically generated vision dataset

• Finetuning Claude to maximise its performance using a particular set of agent tools/skills

• Building a pipeline to ingest and process a novel source of visual training data

• Designing and running experiments to evaluate the scalability of two architectural variants

Logistics

• Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

• 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.

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 can be found on our website.

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Help power the development of Replit Agent as an engineer in the Replit Cloud organisation. The Replit Cloud team builds Replit's first-party cloud infrastructure so users can build, scale, and succeed entirely on Replit. They manage databases, application storage, app publishing and hosting, development/production environment splitting, custom domains, and more. By having a set of first-party services that integrate seamlessly, you will power one of Replit's key product differentiators.

You will:

• Work closely with designers and product managers, to quickly iterate on Replit Cloud to continually grow and improve the product.

• Drive full-stack feature development from conception to deployment, taking ownership of key product initiatives.

• Contribute to architectural decisions that shape the future of our product.

• Ship product and build infrastructure as a true full-stack builder using: TypeScript, React, CSS, Postgres, Go, and Terraform.

Examples of what you could do:

• Leverage our unique cloud infrastructure to build differentiated full product experiences, helping non-technical or semi-technical users remove roadblocks to success.

• Leverage AI agents to proactively optimise or suggest app improvements on latency, reliability, SEO, and more.

• Be part of engineering leadership, steering teams towards the highest impact work and supporting initiatives across the company.

Required skills and experience:

• Bachelor's degree in Computer Science or related field, OR equivalent real-world experience in engineering roles.

• Comfortable building with our tech stack: TypeScript, React, Go

Preferred Qualifications

• Experience building user-facing platform as a service products.

• Experience with AI/agentic systems.

• Previous experience at a high-growth startup.

What we value:

• Problem-solving mindset: Ability to approach complex operational challenges systematically and devise effective solutions

• Self-directed and autonomous: Capable of working independently while collaborating effectively with cross-functional teams

• Strong communication skills: Ability to explain complex technical concepts to both technical and non-technical audiences

• Continuous learning: Passion for staying current with industry best practices and new technologies

• Focus on automation: Strong belief in automating repetitive tasks and building self-healing systems

Full-Time Employee Benefits Include:

• Competitive Salary & Equity

• 401(k) Program with a 4% match

• Health, Dental, Vision and Life Insurance

• Short Term and Long Term Disability

• Paid Parental, Medical, Caregiver Leave

• Commuter Benefits

• Monthly Wellness Stipend

• Autonomous Work Environment

• In Office Set-Up Reimbursement

• Flexible Time Off (FTO) + Holidays

• Quarterly Team Gatherings

• In Office Amenities

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Foster City, CA (Hybrid) In office M,W,F

Employment Type

Full time

Location Type

On-site

Department

EngineeringPlatform

Compensation

• Compensation is determined based on career level, with the base salary for this role ranging from $265K – $390K • Offers Equity

Replit is building the world’s most accessible AI coding agent. Replit Agent can be used by anybody to bring their ideas to life. Whether it’s an app for yourself, the next great startup idea, or a tool to make you more productive at work, Replit Agent can help build it. Replit builds complete apps better than anybody thanks to our full suite of services that handle app integrations, storage, hosting, analytics, and more. We don’t just build apps in development, we handle the full lifecycle into production and beyond.

About the role: Help power the development of Replit Agent as a technical leader for the Replit Cloud organization. You will report to the Vice President of Engineering. The Replit Cloud team builds Replit’s first party cloud infrastructure so users can build, scale, and succeed entirely on Replit. They manage databases, application storage, app publishing and hosting, development/production environment splitting, custom domains, and more. By having a set of first party services that integrate seamlessly, you will power one of Replit’s key product differentiators.

You will:

• Help lead major projects, either by taking new products from 0->1 or doubling down on our first party primitives to keep winning users.
• Work closely with designers and product managers, to quickly iterate on Replit Cloud to continually grow and improve the product.
• Identify the hardest technical and/or quality problems holding us back, and then build solutions.
• Mentor and develop new senior engineers to help grow the team.
• Ship product and build infrastructure as a true full stack builder using: TypeScript, React, CSS, Postgres, Go, and Terraform.

Examples of what you could do:

• Leverage our unique cloud infrastructure to build differentiated full product experiences, helping non-technical or semi-technical users remove roadblocks to success.
• Leverage AI agents to proactively optimize or suggest app improvements on latency, reliability, SEO, and more.
• Be part of engineering leadership, steering teams towards the highest impact work and supporting initiatives across the company.

Required skills and experience:

• Bachelor’s degree in Computer Science or related field, OR equivalent real-world experience in engineering roles
• 10+ years of experience in software with at least 3+ years in a technical leadership role.

Preferred Qualifications

• Experience building user facing platform as a service products.
• Experience with AI/agentic systems.
• Previous experience at a high-growth startup.

_Bonus Points_ :

• Open source project contributions.

What we value:

• Problem-solving mindset: Ability to approach complex operational challenges systematically and devise effective solutions
• Self-directed and autonomous: Capable of working independently while collaborating effectively with cross-functional teams
• Strong communication skills: Ability to explain complex technical concepts to both technical and non-technical audiences
• Continuous learning: Passion for staying current with industry best practices and new technologies
• Focus on automation: Strong belief in automating repetitive tasks and building self-healing systems

Full-Time Employee Benefits Include: 💰 Competitive Salary & Equity 💹 401(k) Program with a 4% match ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚼 Paid Parental, Medical, Caregiver Leave 🚗 Commuter Benefits 📱 Monthly Wellness Stipend 🧑‍💻 Autonomous Work Environment 🖥 In Office Set-Up Reimbursement 🏝 Flexible Time Off (FTO) + Holidays 🚀 Quarterly Team Gatherings ☕ In Office Amenities

Want to learn more about what we are up to?

• Meet the Replit Agent
• Replit: Make an app for that
• Replit Blog
• Amjad TED Talk

Interviewing + Culture at Replit

• Operating Principles
• Reasons not to work at Replit

To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

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Foster City, CA (Hybrid) In office M,W,F

Employment Type

Full time

Location Type

Hybrid

Department

EngineeringPlatform

Compensation

• Compensation is determined based on career level, with the base salary for this role ranging from $300K – $425K • Offers Equity

Replit is building the world’s most accessible AI coding agent. Replit Agent can be used by anybody to bring their ideas to life. Whether it’s an app for yourself, the next great startup idea, or a tool to make you more productive at work, Replit Agent can help build it. Replit builds complete apps better than anybody thanks to our full suite of services that handle app integrations, storage, hosting, analytics, and more. We don’t just build apps in development, we handle the full lifecycle into production and beyond.

About the role:

Help power the development of Replit Agent by leading the Replit Cloud organization. This team builds Replit’s first party cloud infrastructure so users can build, scale, and succeed entirely on Replit. They manage databases, application storage, app publishing and hosting, development/production environment splitting, custom domains, and more. By having a set of first party services that integrate seamlessly, you will power one of Replit’s key product differentiators.

You will:

• Hire, mentor, and retain a high performance team of technically talented, creative, and driven builders. Build a leadership bench to help scale the team.
• Partner with the AI team to automate software maintenance and optimization for non-technical users.
• Be decisive on team strategy and direction, helping Replit achieve company goals and its long term mission of bringing a billion software creators online.
• Set the pace and drive urgency in delivery, to help us win in a hyper competitive market.

Examples of what you could do:

• Leverage our unique cloud infrastructure to build differentiated full product experiences, helping non-technical or semi-technical users remove roadblocks to success.
• Leverage AI agents to proactively optimize or suggest app improvements on latency, reliability, SEO, and more.
• Be part of engineering leadership, steering teams towards the highest impact work and supporting initiatives across the company.

Required skills and experience:

• Bachelor’s degree in Computer Science or related field, OR equivalent real-world experience in security engineering roles
• 10+ years of experience in software with at least 4 years in a management role.

Preferred qualifications:

• Experience building user facing platform as a service products.
• Experience with AI/agentic systems.
• Previous experience at a high-growth startup.

_Bonus points_ :

• Open source project contributions.

What we value:

• Problem-solving mindset: Ability to approach complex operational challenges systematically and devise effective solutions
• Self-directed and autonomous: Capable of working independently while collaborating effectively with cross-functional teams
• Strong communication skills: Ability to explain complex technical concepts to both technical and non-technical audiences
• Continuous learning: Passion for staying current with industry best practices and new technologies
• Focus on automation: Strong belief in automating repetitive tasks and building self-healing systems

_This is a full-time role that can be held from our Foster City, CA office. The hybrid role has an in-office requirement of Monday, Wednesday, and Friday._

Full-Time Employee Benefits Include:

💰 Competitive Salary & Equity

💹 401(k) Program with a 4% match

⚕️ Health, Dental, Vision and Life Insurance

🩼 Short Term and Long Term Disability

🚼 Paid Parental, Medical, Caregiver Leave

🚗 Commuter Benefits

📱 Monthly Wellness Stipend

🧑‍💻 Autonomous Work Environment

🖥 In Office Set-Up Reimbursement

🏝 Flexible Time Off (FTO) + Holidays

🚀 Quarterly Team Gatherings

☕ In Office Amenities

Want to learn more about what we are up to?

• Meet the Replit Agent

• Replit: Make an app for that

• Replit Blog

• Amjad TED Talk

Interviewing + Culture at Replit

• Operating Principles

• Reasons not to work at Replit

To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

Compensation Range: $300K - $425K

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Location

San Francisco

Employment Type

Full time

Department

Data Science

Compensation

• $230K – $385K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance related bonus for eligible employees and benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick and safe time (1 hour per 30 hours worked)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

OpenAI’s Platform team powers how millions of developers and enterprises build with our models. We provide APIs and agentic solutions used by global startups and fortune 500s. We work closely with product, engineering, design, and go-to-market to build a world-class platform that pushes the frontier of AI capabilities.

About the Role

As a Data Scientist on the Platform team, you will drive a data-driven culture for OpenAI’s API and B2B solutions. You’ll define the metrics that matter for developer success and enterprise value, measure the impact of new models and features, and partner with PMs and engineers to improve model quality, reliability, latency, and cost. Your work will shape how thousands of products adopt agentic AI.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will

• Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth

• Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models

• Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products)

• Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams

• Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality)

You might thrive in this role if you have

• 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus)

• Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments

• Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety)

• Strong cross-functional communication with PMs, engineers, and executives

• Strategic instincts beyond p-values—clear thinking about tradeoffs and business impact

You could be an especially great fit if you have

• Background in developer platforms, observability, or usage-based pricing/quotas

• Experience connecting offline evals to online product impact

• Prior work in NLP/LLMs or agentic systems, or in enterprise analytics for B2B products

About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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San Mateo, CA, United States

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.

At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device.

A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.

You Will

As a Senior Machine Learning Engineer on the AI Platform team, you will be a key contributor to building the cutting-edge systems that power AI at Roblox. You will focus on one of three high-impact tracks:

Track 1: AI Platform Projects

• Pioneer next-generation AI tooling to enhance the efficiency, cost, and usability of ML@Roblox.
• Build and maintain core platform components: Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes.
• Design great developer experiences (paved-road templates, tooling, visualizations) to reduce time-to-production and ensure foundational AI systems are scalable and reliable.

Track 2: Distributed Inference & Systems Optimization

• Architect and implement scalable distributed inference systems for efficiently serving LLMs and Large Recommender Models at massive scale.
• Conduct deep, low-level performance analysis and optimize ML models (using techniques like continuous batching, speculative decoding, and quantization) and systems on GPU architectures to maintain peak performance and stability.

Track 3: Information Retrieval & RAG for Gen AI

• Lead the design and development of Retrieval-Augmented Generation (RAG) systems.
• Build and maintain core information retrieval infrastructure—vector databases and knowledge graphs—to enable accurate grounding of Gen AI models.
• Ship language models and 3D objects as a service for the Roblox community, making creation easier.

You Have

• Possessing or pursuing a Ph.D. in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field, with a thesis aligned to Roblox’s research areas.
• Experience with high performance distributed systems, ML Infrastructure, LLM fine tuning/RL, Information Retrieval and Gen AI context generation.
• Expertise in one or more of the following key areas:
• AI/ML Platform Data stores - Features stores, Vector DBs and Knowledge Graphs.
• LLMs - Fine tuning, Safety.
• Agentic systems - Agent evaluation, context engineering.

• Experience building agentic applications with context for real world applications.
• Collaborative mindset and experience integrating and deploying optimized models with cross-functional teams, including data scientists and software engineers.
• Experience with graph databases and large-scale GNNs (Graph Neural Networks)
• Experience working with Kubernetes
• Experience working with one or more cloud providers (e.g., AWS, Azure, GCP)
• Experience working with high availability systems
• Experience working with ML models, LLMs or other AI systems

You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.

As you apply, you can find more information about our process by signing up for Speak\_. You'll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.

For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.

Annual Salary Range

$195,780—$242,100 USD

Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

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Microsoft AI are looking for a talented Member of Technical Staff - Machine Learning Engineer at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI experiences. You'll work directly with leadership to shape the company's direction in the AI and security markets.

About the Role

We are seeking a Senior Machine Learning Engineer to tackle some of the hardest problems at the intersection of applied ML, AI security, and agentic systems. This is a hands-on role focused on designing, training, evaluating, and shipping ML-powered defenses that protect Copilot users from threats such as prompt injection, adversarial manipulation, unsafe delegation, and abuse of agentic workflows.

Accountabilities

• Design, train, and deploy ML-based defenses for threats such as prompt injection, adversarial inputs, and abuse of agentic workflows.
• Develop adaptive detection and policy models that learn from evolving attacker behavior rather than relying solely on static rules or signatures.

The Candidate we're looking for

Experience:

• 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Solid foundation in ML fundamentals, including classification, anomaly detection, representation learning, and model evaluation.
• Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow).

Personal attributes:

• Ability to reason about adversarial behavior, threat models, and failure modes in AI/ML systems.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.

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Microsoft AI are looking for a talented Member of Technical Staff - Machine Learning Engineer at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI experiences. You'll work directly with leadership to shape the company's direction in the AI and security markets.

About the Role

We are seeking a Senior Machine Learning Engineer to tackle some of the hardest problems at the intersection of applied ML, AI security, and agentic systems. This is a hands-on role focused on designing, training, evaluating, and shipping ML-powered defenses that protect Copilot users from threats such as prompt injection, adversarial manipulation, unsafe delegation, and abuse of agentic workflows.

Accountabilities

• Design, train, and deploy ML-based defenses for threats such as prompt injection, adversarial inputs, and abuse of agentic workflows.
• Develop adaptive detection and policy models that learn from evolving attacker behavior rather than relying solely on static rules or signatures.

The Candidate we're looking for

Experience:

• 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Solid foundation in ML fundamentals, including classification, anomaly detection, representation learning, and model evaluation.
• Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow).

Personal attributes:

• Ability to reason about adversarial behavior, threat models, and failure modes in AI/ML systems.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.

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Microsoft AI are looking for a talented Member of Technical Staff - Machine Learning Engineer at their New York office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI experiences. You'll work directly with leadership to shape the company's direction in the AI and security markets.

About the Role

We are seeking a Senior Machine Learning Engineer to tackle some of the hardest problems at the intersection of applied ML, AI security, and agentic systems. This is a hands-on role focused on designing, training, evaluating, and shipping ML-powered defenses that protect Copilot users from threats such as prompt injection, adversarial manipulation, unsafe delegation, and abuse of agentic workflows.

Accountabilities

• Design, train, and deploy ML-based defenses for threats such as prompt injection, adversarial inputs, and abuse of agentic workflows.
• Develop adaptive detection and policy models that learn from evolving attacker behavior rather than relying solely on static rules or signatures.

The Candidate we're looking for

Experience:

• 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Solid foundation in ML fundamentals, including classification, anomaly detection, representation learning, and model evaluation.
• Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow).

Personal attributes:

• Ability to reason about adversarial behavior, threat models, and failure modes in AI/ML systems.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.

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