This is a highly specialized role sitting at the intersection of model behaviour and product quality. You'll be the expert on how Claude behaves inside Claude Code, owning and maintaining the system prompts that ship with each new model snapshot. When a new model drops, you're the person making sure Claude Code feels right within days , not weeks.

You'll work closely with Model Quality and Research to understand emergent behaviours and behavioural regressions, and with product and safeguards teams to respond quickly when something goes wrong.

This role requires someone who can move fast on behavioural tuning while maintaining rigor, and who cares deeply about the end-to-end developer experience Claude Code delivers. You'll need strong prompting skills, excellent judgment about model behaviours, and the collaborative skills to work across product, safeguards, and research teams.

Responsibilities:

• Own Claude Code's system prompts for each new model snapshot, ensuring behaviours feel consistent and well-tuned
• Review production prompt changes and serve as a resource for particularly challenging prompting problems involving alignment and reputational risks
• Lead incident response for behavioural and policy concerns, coordinating with product and safeguards teams
• Scale prompting and evaluation best practices across claude code and product teams.
• Deliver product evaluations focused on model behaviours
• Define and streamline processes for rolling out prompt changes, including launch criteria and review practices
• Create model-specific prompt guides that document quirks and optimal prompting strategies for each release
• Collaborate with product teams to translate feature requirements into effective prompts

You may be a good fit if you:

• Are a power user of agentic coding tools and have strong intuition about model capabilities and limitations
• Thrive in high-intensity environments with fast iteration cycles
• Take full ownership of problems and drive them to completion independently
• Are skilled at creating and maintaining behavioural evaluations
• Have strong technical understanding, including comprehension of agent scaffold architectures and model training processes
• Are an experienced coder comfortable working in Python and Typescript
• Have independently driven changes through production systems with strong execution and responsiveness
• Have experience translating user feedback and product needs into coherent prompts and behavioural specifications
• Excel at working across organisational boundaries, collaborating effectively with teams that have differing goals and perspectives
• Have experience translating user feedback and behavioural observations into coherent prompt changes and specifications
• Care deeply about AI safety and making Claude a healthy alternative in the AI landscape

Annual compensation range for this role is $300,000-$405,000 USD.

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In this role, you'll oversee the product roadmap for your data vertical, owning 'data as a product', pipelines for data generation and quality, and researcher-facing tools that help labs train and evaluate intelligent agents in complex environments.

You'll work directly with Scale's most important customers and their leading researchers, representing Scale as the technical expert for your products and influencing both internal and external roadmaps.

The ideal candidate brings together a strong entrepreneurial & go-to-market mindset, technical depth, and a sense for AI research, enabling them to get in front of technical stakeholders to drive mission-critical outcomes.

Responsibilities:

• Own the roadmap for the Agent & RL Environment Data vertical, setting product direction and driving execution across engineering, operations, and go-to-market teams.

• Build technical partnerships with research teams at leading AI labs, identifying insights that shape new product lines and competitive strategies for your vertical.

• Design, experiment with, and deliver high-quality data pipelines, tooling, and evaluation frameworks that advance RL and agentic model capabilities.

• Scope out and scale the creation of RL environments that simulate real-world use cases.

• Collaborate cross-functionally, influencing business priorities and diving in the weeds of research, operations, and customer interactions.

Ideally, You'd Have:

• Entrepreneurial mindset: A builder excited by ambiguity and motivated to create new products from the ground up.

• 6+ years of experience in product management or a customer-facing role.

• Technical fluency: Software engineering background (a degree in computer science or equivalent experience).

• Understanding of reinforcement learnings, simulation environments, or data pipelines for model training and evaluation

• Strong customer intuition and the ability to translate technical requirements into impactful product decisions.

• Bias for action and comfort wearing multiple hats and operating in fast-moving environments.

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

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As a Senior AI Infrastructure Engineer focused on model training and inference, you will:

Implement and scale training pipelines for large transformer and LLM models, from data ingestion and preprocessing through distributed training and evaluation.

Build and optimize inference services that deliver low-latency, high-reliability experiences for our customers, including autoscaling, routing, and fallbacks.

Work on GPU-level performance: tuning kernels, improving utilization, and identifying bottlenecks across our training and inference stack.

Collaborate closely with ML scientists to implement cutting edge training and inference methods and bring them to production.

Play an active role in hiring, mentoring, and developing other engineers on the team.

Raise the bar for technical standards, reliability, and operational excellence across Intercom’s AI platform.

We’re looking to hire Senior+ AI Infrastructure Engineers. You’re likely a great fit if:

You have 5+ years of experience in software engineering, with a strong track record of shipping high-quality products or platforms.

You hold a degree in Computer Science, Computer Engineering, or a related field (or you have equivalent experience with very strong fundamentals).

You have hands-on experience with one or more of the following:

Model training (especially transformers and LLMs).

Model inference at scale (again, especially transformers and LLMs).

Low-level GPU work, such as writing CUDA or Triton kernels.

Comfortable working in production environments at meaningful scale (traffic, data, or organizational).

You communicate clearly, can explain complex technical topics to different audiences, and enjoy close collaboration with both engineers and non-engineers.

You take pride in strong technical fundamentals, love learning, and are willing to invest in your own development.

Have deep knowledge of at least one programming language (for example Python, Ruby, Java, Go, etc.). Specific language experience is less important than your ability to write clean, reliable code and learn new stacks quickly.

We are a well-treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us!

Competitive salary, annual bonus and equity

Regular compensation reviews - we reward great work!

Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated.

Generous paid time off above statutory minimum

Hybrid working

MacBooks are our standard, but we also offer Windows for certain roles when needed.

Fun events for employees, friends, and family!

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You will partner with engineering teams within W&B and CoreWeave AI/ML Platform Services (AMPS) to ensure W&B integrates seamlessly into the broader ML ecosystem, while maintaining high reliability and predictable releases.

This role is ideal for someone who thrives in cross-functional environments, has a strong grasp of developer workflows, and excels at creating repeatable, reliable program structures that scale.

Responsibilities

• Drive end-to-end program management for critical platform initiatives.
• Build and run release management processes, ensuring predictable and high-quality delivery cycles.
• Partner with engineering and product to define success metrics, manage risks, and ensure on-time delivery.
• Build and scale incident management and RCA processes for W&B services.
• Improve the predictability and visibility of releases across teams, introducing dashboards, retrospectives, and program forums.
• Collaborate with TPMs and engineering leaders across W&B and CoreWeave to ensure end-to-end reliability across the ML developer stack.

Qualifications

• Bachelor's degree in a technical field or equivalent experience.
• 5+ years of program management experience in SaaS, developer tools, or ML/AI platforms.
• Proven experience running release management programs and incident management processes.
• Strong technical fluency in cloud computing, developer workflows, and CI/CD practices.
• Excellent communication and facilitation skills with diverse technical and non-technical audiences.
• Track record of improving reliability, efficiency, and predictability in software delivery.

Additional Qualifications

• Familiarity with ML workflows, model training/inference, and developer productivity tools.
• Experience building integrations between SaaS platforms, APIs, and cloud services.
• Strong background in reliability engineering practices and DevOps program leadership.

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We are seeking a highly organized and technically skilled individual with hands-on experience designing processes, implementing, managing, and integrating legal systems with enterprise platforms. The ideal candidate will have a proven track record of evaluating technology, driving automation initiatives, and delivering measurable improvements in legal workflows.

As a Legal Operations Analyst, you will serve as a co-administrator for Ironclad, managing legal workflows, templates, clause libraries, reporting, and user access. You will facilitate end-to-end contract processes, track milestones, and ensure timely approvals. You will also help pilot, implement, and optimize AI and automation tools to streamline legal workflows and enhance productivity.

This highly impactful role offers the opportunity to shape contract management, drive adoption of AI and automation, and help scale the LPT department's operations in a fast-paced, evolving environment.

Responsibilities:

• CLM Administration: Serve as a co-administrator for Ironclad, managing legal workflows, templates, clause libraries, reporting, and user access.
• AI & Technology Initiatives: Help pilot, implement, and optimize AI and automation tools to streamline legal workflows and enhance productivity.
• Process Improvement: Identify opportunities to streamline in contract and workflow processes, recommend solutions, and help implement best practices to scale the legal function.
• Project Management: Support projects end-to-end – from planning and coordination to rollout and adoption.
• Analytics & Reporting: Build dashboards and reports on contract metrics, KPIs, and technology adoption metrics to maintain data for leadership review.
• Training & Enablement: Develop documentation and training for LPT teams and business partners to maximize adoption of CLM and AI tools.
• General Legal Ops Support: Ensure smooth execution of department workflows by supporting day-to-day operations, including maintaining knowledge bases, driving cross-functional initiatives, and supporting strategic ad hoc projects.

Requirements:

• 5+ years of experience in legal operations, preferably at a fast-paced global technology company.
• Highly organized and proven in defining and executing a project from start to finish, ability to manage multiple concurrent projects, high-volume workloads, and shifting priorities with confidence.
• Strong technical acumen with hands-on experience designing processes, implementing, managing, and integrating legal systems with enterprise platforms.
• Proven track record of evaluating technology, driving automation initiatives, and delivering measurable improvements in legal workflows.
• Skilled in legal data analytics (ROI, cycle times, volumes, trends).
• Excellent communicator with strong writing skills; able to present complex issues clearly and concisely.
• Collaborative, adaptable, and cross-functional team player with integrity, curiosity, and strong interpersonal skills – with the ability to work independently or cross-functionally.

Bonus:

• Working knowledge of AI tools and applications, including prompt design, data extraction, document analysis, and model training.
• A sense of humor!

Compensation:

• Compensation may be adjusted based on location: For the New York, D.C., and California (Excluding the bay area) the expected salary range is $124,000 - $152,000
• Equity: This role is eligible to participate in Cloudflare’s equity plan.
• Benefits: Cloudflare offers a complete package of benefits and programs to support you and your family, including health and welfare benefits, financial benefits, and time off.

What Makes Cloudflare Special?

• We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul.
• Fundamental to our mission to help build a better Internet is protecting the free and open Internet.
• Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.
• Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration.
• 1.1.1.1: We released 1.1.1.1, a free public DNS resolver that blocks ads and trackers, making the Internet faster and safer for everyone.

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The design space of biomolecules is unimaginably vast , far beyond what can be explored experimentally. Yet within this space lie molecules with properties essential for new medicines. Our machine learning models learn to design therapeutic biomolecules with specific, desirable functions.

We advance the state of the art in molecular design by training large-scale foundation models and developing cutting-edge generative approaches. The models learn from diverse heterogeneous datasets and are refined through focused fine-tuning and feedback from experiments. Key to progress is a team that combines exceptional machine learning expertise with thorough domain understanding.

You will collaborate closely with other machine learning researchers and engineers, as well as computational and experimental biologists, to advance these models and translate their capabilities into real therapeutic designs.

Responsibilities

• Embody our vision of an interdisciplinary environment and embrace learning about areas outside of your traditional area of expertise

• Develop, implement, train, and iteratively improve state-of-the-art models for biomolecule design

• Analyze, visualize, and communicate results to support team efforts in improving models and data

• Create, deploy, and refine tools for efficient, reliable machine learning experimentation and production

• Work with biologists to collect data for the training and evaluation of generative models of biomolecules

• Provide mentorship and technical direction to team members as appropriate

Qualifications

• 3+ years of hands-on experience developing ML models

• Demonstrated track record of implementing, training, improving advanced machine learning models

• Highly capable programmer fluent in Python ecosystem and PyTorch or similar deep learning framework

• Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET

• Readiness to travel several times a year for company retreats and business events

Compensation

$200K – $275K + Bonus + Equity

Benefits

• A competitive compensation package

• 30 days paid vacation per year

• Comprehensive health insurance for US based employees

• 401K with company match for US based employees and Direktversicherung for German employees

• Quarterly company-wide retreats

• Monthly wellness benefit

• Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland

• Learning & Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning & Development platform EdX and Hone

• A buddy to help you get settled

At Inceptive, we are creating tools to develop increasingly powerful biological software for the rational design of novel, broadly accessible medicines and biotechnologies previously out of reach. Our team brings together vast expertise in molecular biology, machine learning, and software engineering, and we are all working towards becoming interdisciplinary, meaning we deepen the knowledge we have in our area of expertise while also expanding our knowledge of completely new fields.

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Your responsibilities will include designing and implementing platform capabilities to support the AI/ML development and productionization lifecycle, including training, evaluation, deployment, monitoring, and management of models and agents.

You will also design and implement platform integrations with various frameworks in the AI/ML ecosystem, collaborate with the AI/ML community across the world to advance the state-of-the-art in AIOps, and ensure the latest AI/ML tooling advancements are available to Databricks' customers.

Additionally, you will mentor and guide junior engineers on the team by helping with project planning, technical decisions, and code and document review.

We are looking for a highly skilled and experienced software engineer with a strong background in AI/ML and a passion for building and maintaining open-source platforms.

The ideal candidate will have a BS (or higher) in Computer Science, or a related field, and 5+ years of hands-on experience in building production systems using at least one of the following programming languages: Python (Preferred), Scala and Java.

Experience building and maintaining software tools and frameworks for AI/ML, ideally in an open-source environment, is also required.

Familiarity with AI/ML and AIOps concepts and technologies, such as model training, deployment, and monitoring, is essential.

A deep understanding and experience in working with agent frameworks such as LangChain, LlamaIndex, DSPy, or other similar projects is preferred.

Significant contributions to open-source projects in the AI/ML domain, such as SparkML, TensorFlow, PyTorch, MLflow, or other similar projects, are also preferred.

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.

For specific details on the benefits offered in your region, please click here.

We are committed to diversity and inclusion and welcome applications from candidates of all backgrounds.

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Anthropic's sandboxing infrastructure enables Claude to safely execute code and interact with external systems. As we expand Claude's capabilities, the reliability, security, and developer experience of this infrastructure becomes increasingly critical. We're looking for an engineer to join the sandboxing team and help shape both the client-side library/API and the underlying infrastructure.

In this role, you'll combine deep infrastructure expertise with an obsession for developer experience. You'll help maintain and evolve a system that must be correct, performant, and intuitive to use. You'll work closely with internal teams to understand their needs, burn down errors and edge cases, and build a roadmap that anticipates where the product needs to go. This is a role for someone who finds satisfaction in both the craft of building reliable systems and the empathy required to serve developers and researchers well.

Responsibilities

• Contribute to the client library, API surface, and underlying infrastructure for Anthropic's sandboxing system, ensuring it is reliable, well-documented, and intuitive to use
• Drive down error rates and improve correctness through systematic debugging, monitoring, and proactive fixes
• Help develop and maintain a product roadmap for sandboxing capabilities, balancing immediate needs with long-term architectural improvements
• Partner closely with internal teams using the sandboxing system to understand their requirements, debug issues, and build tooling that serves their use cases
• Respond to incidents and production issues with urgency, conducting thorough root cause analysis and implementing preventive measures
• Build comprehensive testing, observability, and documentation to ensure the system meets a high quality bar
• Collaborate across the sandboxing team, flexing between client-side and infrastructure work as needed

You May Be a Good Fit If You

• Have 5+ years of software engineering experience, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs
• Obsess over developer experience,you've thought deeply about API design, error propagation, documentation, and the small details that make a library feel well-crafted
• Have experience operating complex distributed systems
• Bring a track record of systematically improving reliability,you've burned down error budgets, built monitoring, and driven issues to resolution
• Can develop and articulate a long-term vision for a product, translating user feedback and technical constraints into a coherent roadmap
• Are comfortable with ambiguity and can context-switch between reactive incident work and proactive product development
• Communicate clearly with both technical and non-technical stakeholders

Strong Candidates May Also Have

• Experience as a founder or early engineer at an infrastructure-focused startup, where you owned a product end-to-end
• Background in security, sandboxing, or isolation technologies (containers, VMs, seccomp, namespaces, etc.)
• Open-source contributions in the Python ecosystem
• Experience building developer tools, CLIs, or platforms used by other engineers
• History of working on incident response and on-call rotations for production systems
• Exposure to reinforcement learning or model training infrastructure

Representative Projects

These are examples of past work that would indicate a good fit,not a description of the role itself:

• Maintaining an open source SDK through multiple major version upgrades while minimizing breaking changes for users
• Leading an initiative to reduce P0 incidents by XX% through improved error handling, retries, and observability
• Building a developer platform at a startup from zero to product-market fit, iterating based on user feedback
• Embedding with an internal team for a quarter to deeply understand their workflows and shipping targeted improvements to a piece of infrastructure they rely on
• Developing a multi-quarter roadmap for a developer tools product, balancing user requests with technical debt reduction

Logistics

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

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The impact you'll have:

• Design and implement platform capabilities to support the AI/ML development and productionization lifecycle including training, evaluation, deployment, monitoring, and management of models and agents
• Design and implement platform integrations with various frameworks in the AI/ML ecosystem
• Collaborate with the AI/ML community across the world to advance the state-of-the-art in AIOps
• Ensure the latest AI/ML tooling advancements are available to Databricks' customers, thereby enabling organizations around the world to get more value from their data
• Mentor and guide junior engineers on the team by helping with project planning, technical decisions, and code and document review

What we look for:

• BS (or higher) in Computer Science, or a related field
• 3+ years of hands-on experience in building production systems using at least one of the following programming languages: Python (Preferred), Scala and Java
• Experience building and maintaining software tools and frameworks for AI/ML, ideally in an open-source environment
• Familiarity with AI/ML and AIOps concepts and technologies, such as model training, deployment, and monitoring
• Deep understanding and experience in working with agent frameworks such as LangChain, LlamaIndex, DSPy, or other similar projects
• Significant contributions to open-source projects in the AI/ML domain, such as SparkML, TensorFlow, PyTorch, MLflow, or other similar projects

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide , including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 , rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

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As a Software Engineer on Anthropic's Human Data Interfaces team, you'll own the architecture and execution of our data collection pipelines, designing systems that are both performant at scale and resilient to the rapidly changing needs of our research teams.

Responsibilities

• Architect and build data collection pipelines that support rapid iteration, balancing data quality and system maintainability
• Think deeply about the experience of the crowdworkers and vendors using these systems, building interfaces that are clear, efficient, and lead to high-quality data
• Collaborate closely with research teams to understand evolving data needs and iterate quickly on collection methods
• Partner with our Human Data Operations team to understand the end-to-end data workflow and design interfaces that make their jobs easier
• Prioritize and juggle multiple workstreams, making trade-off decisions in a fast-moving environment where research priorities can shift quickly

You May Be a Good Fit If You:

• Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well
• Are a strong full-stack engineer with broad experience across the stack
• Are very good at building internal tools, including working with users of the tools to understand their needs
• Thrive in fast-moving environments where you need to balance speed of iteration with long-term system health
• Are a quick study,this team sits at the intersection of a large number of different complex technical systems that you'll need to understand (at a high level) to be effective

Strong Candidates May Also Have:

• Experience building human data labelling interfaces, human-in-the-loop systems, or data collection pipelines
• Familiarity with how preference data and reward models are used in AI model training
• Experience working with researchers who are internal users/customers
• Background in building, and improving the user-experience of user-facing applications, particularly those involving complex UI interactions or annotation workflows
• Strong instincts around system design , building things that evolve gracefully as requirements change
• Experience influencing technical and product direction on a team

Logistics

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

Benefits

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

How to Apply

If you're interested in this role, please submit your application through our website. We look forward to hearing from you!

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To be successful in this role, you will need 5+ years of experience in ML infrastructure, including model training and model deployments, hands-on experience with ML optimization, deep experience with cloud-based technologies, and proficiency with common programming languages and frameworks of ML. You should also have strong organizational and communication skills, experience working with graph databases and graph neural networks, and a deep understanding of the machine learning development lifecycle.

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. 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.

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We are looking for an experienced engineer with 8+ years of experience in ML infrastructure, including model training and model deployments. You should have hands-on experience with ML optimization, cloud-based technologies, MLOps tools, and proficiency with common programming languages and frameworks of ML. Strong focus on scalability, reliability, performance, and ease of use is essential.

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. 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.

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This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to research direction. You'll work on fundamental research in reinforcement learning, designing training environments and methodologies that push the state of the art, and building evaluations that measure genuine capability.

Responsibilities:

• Build the next generation of agentic environments
• Build rigorous evaluations that measure real capability
• Collaborate across research and infrastructure teams to ship environments into production training
• Debug and iterate rapidly across research and production ML stacks
• Contribute to research culture through technical discussions and collaborative problem-solving

You may be a good fit if you:

• Are highly impact-driven , you care about outcomes, not activity
• Operate with high agency
• Have good research taste or senior technical experience, demonstrating good judgment in identifying what actually matters in complex problem spaces
• Can balance research exploration with engineering implementation
• Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems
• Are comfortable with uncertainty and adapt quickly as the landscape shifts
• Have strong software engineering skills and can build robust infrastructure
• Enjoy pair programming (we love to pair!)

Strong candidates may also have one or more of the following:

• Have industry experience with large language model training, fine-tuning or evaluation
• Have industry experience building RL environments, simulation systems, or large-scale ML infrastructure
• Senior experience in a relevant technical field even if transitioning domains
• Deep expertise in sandboxing, containerization, VM infrastructure, or distributed systems
• Published influential work in relevant ML areas

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

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In this role, you will specialize in improving and optimizing our ads auction and pricing mechanism which will have a direct impact on upleveling the utility for both our advertiser and user values. You will also have the opportunity to work on other org-wide strategic initiatives such as supply optimization and ad relevance, where you will drive and execute on Reddit’s vision to transform Reddit into an advertising platform that shows the right ads to the right users at the right time in the right context.

As a Staff Machine Learning Engineer in the Ads Marketplace Quality team, you will be an industry technical leader with domain knowledge in ads marketplace dynamics, auction and pricing, you will research, formulate, and execute on our mission to build end-to-end algorithmic solutions and deliver values to all the three-sided participants to our marketplace.

Responsibilities:

• Lead and oversee the strategy development, quarterly planning and day-to-day execution of initiatives related to ads marketplace, auction and pricing.
• Proactively further our understanding of marketplace dynamics and develop algorithms to improve the efficiency and effectiveness of our ads marketplace, auction and pricing.
• Oversee end-to-end ML workflows,from data ingestion and feature engineering to model training, evaluation, and deployment,that optimizes the ads marketplace efficiency.
• Be a mentor, lead both junior and senior engineers in implementing technical designs and reviews. Fostering a culture of innovation, technical excellence, and knowledge sharing across the organization.
• Be a cross-functional advocate for the team, collaborate with cross-functional teams (e.g., product management, data science, PMM, Sales etc.) to innovate and build products.

Required Qualifications:

• 8+ years of experience with industry-level product development, with at least 5+ years focused on data-driven, marketplace-optimization problem space at scale.
• Strong knowledge of ads marketplace optimization. Demonstrated experience architecting ads marketplace design, improving and optimizing ads auction and pricing mechanisms.
• Solid understanding of large-scale data processing, distributed computing, and data infrastructure (e.g., Spark, Kafka, Beam, Flink).
• Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries for feature engineering, model training, and inference.
• Proficiency with programming languages (Java, Python, Golang, C++, or similar) and statistical analysis.
• Proven technical leadership in cross-functional settings, driving architectural decisions and influencing stakeholders (product, data science, privacy, legal).
• Excellent communication, mentoring, and collaboration skills to align teams on a long-term vision for ads marketplace optimization.

Benefits:

• Comprehensive Healthcare Benefits
• 401k Matching
• Workspace benefits for your home office
• Personal & Professional development funds
• Family Planning Support
• Flexible Vacation (please use them!) & Reddit Global Wellness Days
• 4+ months paid Parental Leave
• Paid Volunteer time off

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This is a highly specialized role sitting at the intersection of model behaviour and product quality. You'll be the expert on how Claude behaves inside Claude Code, owning and maintaining the system prompts that ship with each new model snapshot. When a new model drops, you're the person making sure Claude Code feels right within days , not weeks.

You'll work closely with Model Quality and Research to understand emergent behaviours and behavioural regressions, and with product and safeguards teams to respond quickly when something goes wrong.

This role requires someone who can move fast on behavioural tuning while maintaining rigor, and who cares deeply about the end-to-end developer experience Claude Code delivers. You'll need strong prompting skills, excellent judgment about model behaviours, and the collaborative skills to work across product, safeguards, and research teams.

Responsibilities:

• Own Claude Code's system prompts for each new model snapshot, ensuring behaviours feel consistent and well-tuned
• Review production prompt changes and serve as a resource for particularly challenging prompting problems involving alignment and reputational risks
• Lead incident response for behavioural and policy concerns, coordinating with product and safeguards teams
• Scale prompting and evaluation best practices across claude code and product teams.
• Deliver product evaluations focused on model behaviours
• Define and streamline processes for rolling out prompt changes, including launch criteria and review practices
• Create model-specific prompt guides that document quirks and optimal prompting strategies for each release
• Collaborate with product teams to translate feature requirements into effective prompts

You may be a good fit if you:

• Are a power user of agentic coding tools and have strong intuition about model capabilities and limitations
• Thrive in high-intensity environments with fast iteration cycles
• Take full ownership of problems and drive them to completion independently
• Are skilled at creating and maintaining behavioural evaluations
• Have strong technical understanding, including comprehension of agent scaffold architectures and model training processes
• Are an experienced coder comfortable working in Python and Typescript
• Have independently driven changes through production systems with strong execution and responsiveness
• Have experience translating user feedback and product needs into coherent prompts and behavioural specifications
• Excel at working across organisational boundaries, collaborating effectively with teams that have differing goals and perspectives
• Have experience translating user feedback and behavioural observations into coherent prompt changes and specifications
• Care deeply about AI safety and making Claude a healthy alternative in the AI landscape

Annual compensation range for this role is $300,000-$405,000 USD.

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As a senior machine learning engineer, you will play a key role in the end-to-end design and implementation of our product, which is a platform for powering use cases across training and serving of generative AI models. You will work closely with both customers and internal ML researchers to identify key areas of development for our generative AI platform.

Key responsibilities include:

• Designing and building the core platform infrastructure that supports our customer-facing product features
• Ensuring the reliability, security, and scalability of the backend distributed systems that power all aspects of our product
• Translating product requirements into user interfaces and backend distributed system design and owning end-to-end implementation

We look for:

• 4+ years of hands-on programming experience with at least one modern language such as Python, Scala, Go, or C++
• Strong sense of distributed systems design and experience building large-scale systems
• Experience building ML platform systems for applications in the ML model development lifecycle such as data preparation, model training, model evaluation, and model serving
• Direct experience developing ML models is a plus but not required
• Strong sense of end-to-end product ownership as well as intuition for both robust system design and product usability
• Effective communication skills and the ability to articulate complex technical ideas to cross-disciplinary internal and external stakeholders

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

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In this role, you will leverage your expertise in regulatory compliance, contract analysis, legal research, and dispute resolution to support the training of AI systems. You will collaborate with technical teams to refine annotation tools and curate impactful data, ensuring our models effectively capture real-world legal and compliance dynamics.

Responsibilities:

• Utilize proprietary software to provide accurate input and labels for legal and compliance projects, ensuring high-quality data for AI model training.
• Deliver curated, high-quality data for scenarios involving regulatory compliance, contract analysis, legal research, and dispute resolution.
• Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies.
• Assist in designing and improving efficient annotation tools tailored for legal and compliance data.
• Select and analyze complex problems in legal and compliance fields aligned with your expertise to enhance AI model performance.
• Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability.

Basic Qualifications:

• Must have a J.D. (Juris Doctor) or foreign equivalent.
• At least 2 years of practicing law in one or more of the following practice areas: Criminal Law, Civil Litigation, Torts, International Law, Health Law, Civil Rights Law, Constitutional Law, Construction Law, Education Law, Employment and Labor Law, Environmental Law, Corporate Law, Business Law, Family Law, Immigration Law, Intellectual Property Law, Patent Law, Real Estate Law, Tax Law, Bankruptcy Law, Administrative Law, Antitrust Law, Privacy and Data Protection Law, Cybersecurity Law, Energy Law.
• Strong legal analysis and writing skills, including the ability to draft clear, concise, and well-reasoned legal documents and memoranda
• Proficiency in reading and writing informal and professional English.
• Strong communication, interpersonal, analytical, and organizational skills.
• Excellent reading comprehension and ability to exercise autonomous judgment with limited data.
• Passion for technological advancements and innovation in legal processes.
• Relevant certification, license, or advanced training (bar admission or similar legal certification)

Preferred Skills and Experience:

• Experience mentoring or training others in legal practices.
• Comfort with recording audio or video sessions for data collection.
• Familiarity with AI or data annotation workflows in a technical setting.

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In this role, you will leverage your expertise in mergers, acquisitions, divestitures, financial modeling, valuation techniques, deal structuring, due diligence, pitch books, and fairness opinions to support the training of AI systems.

Responsibilities:

• Utilize proprietary software to provide accurate input and labels for M&A investment banking projects, ensuring high-quality data for AI model training.
• Deliver curated, high-quality data for scenarios involving mergers, acquisitions, divestitures, financial modeling, valuation techniques (e.g., DCF, comparables, precedent transactions), deal structuring, due diligence, pitch books, and fairness opinions.
• Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies.
• Assist in designing and improving efficient annotation tools tailored for M&A investment banking data.
• Select and analyze complex problems in M&A investment banking fields aligned with your expertise to enhance AI model performance.
• Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability.

Basic Qualifications:

• Professional experience in M&A investment banking or related fields (e.g., M&A advisor, analyst, associate, vice president or director in investment banking focused on mergers and acquisitions).
• Proficiency in reading and writing informal and professional English.
• Strong communication, interpersonal, analytical, and organizational skills.
• Excellent reading comprehension and ability to exercise autonomous judgment with limited data.
• Passion for technological advancements and innovation in M&A investment banking.

Preferred Skills and Experience:

• Relevant certification or advanced training (e.g., Series 7, Series 63, Series 79, CFA, or similar finance-related certification).
• Experience mentoring or training others in M&A investment banking practices, such as financial modeling, valuation, or deal execution.
• Comfort with recording audio or video sessions for data collection.
• Familiarity with AI or data annotation workflows in a technical setting.

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
• For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time.
• We are unable to provide visa sponsorship.
• For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US based candidates: $45/hour - $100/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.

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The Technical Advisor Specialist (Part-Time Internship) role is a summer semester opportunity designed for university students, ideally with experience in competitive coding, mathematics, and STEM disciplines.

These Specialists will immerse themselves in real-world projects that push the boundaries of generative AI, gaining firsthand exposure to cutting-edge research and technology.

Throughout the program, you’ll have the freedom to work flexibly around your academic schedule, the chance to connect directly with AI experts, and the support of a team that values your contributions and professional growth.

What You'll Do

• Contribute to Cutting-Edge AI Projects: Work on initiatives aimed at advancing AI capabilities,such as training models for complex reasoning tasks or identifying model failure modes.

You’ll gain exposure to state-of-the-art technologies and research, enhancing your technical expertise.

• Join Focus Groups: Participate in bi-weekly sessions where you’ll exchange insights, discuss evolving AI techniques, and learn from experienced researchers.

This forum encourages deep exploration of topics and helps you develop critical thinking and communication skills.

• Engage in Team-Based Projects: Collaborate with small groups of specialists on creative challenges,ranging from drafting blog-style content to conceptualizing innovative AI solutions.

By working closely with peers, you’ll refine your teamwork, leadership, and problem-solving abilities.

• Work Independently & Flexibly: Set your own working hours, ensuring you can prioritize your academic life while still making meaningful progress.

The environment is structured to accommodate your schedule without compromising the quality of your contributions.

Who Should Apply

• Academic Background: Enrolled students in computer science, mathematics, engineering, or a related STEM field.

• Technical Skills: Demonstrated coding proficiency, strong analytical abilities, or experience with competitive math or programming competitions.

• Mindset: Curious, self-motivated, and eager to learn, contribute, and collaborate with like-minded peers and industry experts.

Why Join Us?

• Real-World Impact: Your work will have tangible influence on the direction of AI capabilities, giving you a sense of purpose and involvement that goes beyond typical internship work.

• Professional Growth & Networking: Connect one-on-one with AI professionals, build relationships with fellow specialists, and expand your industry network.

• Optional In-Person Meetups: Opt to join occasional regional gatherings to meet peers and Scale AI personnel face-to-face.

These events provide opportunities for more personal interactions, fostering deeper connections and insights that complement your remote work.

• Pathways to the Future: Exceptional specialists may be invited to continue working with Scale AI.

Alumni networks and ongoing support keep doors open for future collaborations and career advancement.

• Compensation & Flexibility: $50/hour; 5-20 hours a week, and fully remote (within the U.S.)

Notes

Our policy requires a 90-day waiting period before reconsidering candidates for the same role.

This allows us to ensure a fair and thorough evaluation of all applicants.

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Your role involves refining annotation tools and selecting complex problems from advanced finance fields, with a focus on investment analysis and topics including but not limited to equities, commodities, real estate, fixed income, forex, derivatives, and accounting. Your expertise can drive significant improvements in model performance.

This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial.

As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI's AI models. AI Tutors teach our AI models about how people interact and react, as well as how people approach issues and discussions in finance.

Responsibilities:

• Use proprietary software applications to provide input/labels on defined projects.
• Support and ensure the delivery of high-quality curated data.
• Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interact with the technical staff to help improve the design of efficient annotation tools.
• Choose problems from finance fields that align with your expertise, focusing on areas like investment analysis, taxation, accounting, financial modeling, or risk assessment where you can confidently provide detailed solutions and evaluate model responses.

Basic Qualifications:

• Must possess a Master's or PhD in a finance-related field (Finance, Economics, Business Administration with a finance focus, or related disciplines) or equivalent professional experience as an investment analyst specializing in equity, commodities, real estate, fixed income, or accounting.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various financial information resources, databases, and online resources (e.g., Bloomberg, Reuters, SEC filings).
• Outstanding communication, interpersonal, analytical, and organizational capabilities.
• Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material.
• Strong passion for and commitment to technological advancements and innovation in finance.

Preferred Skills and Experience:

• Professional experience as an investment analyst, portfolio or wealth manager, or financial consultant.
• Possesses experience with at least one publication in a reputable finance or economics journal or outlet.
• Teaching experience (as a professor, teacher, or tutor) in finance-related subjects.
• Corporate accountants with a CPA - CFA Charterholder

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

As a Fellow, you will receive:

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

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

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

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

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

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

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

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

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You will work on the most critical modelling challenges at any given time. You will get clarity on your first project before an offer.

Responsibilities

• Work on the most critical modelling challenges at any given time
• Get clarity on your first project before an offer

Basic Qualifications

• Believe truth-seeking AI is the most important and challenging problem
• Be obsessed about building incredibly useful models
• Be a power user of AI models
• Have previously trained models used by millions of people (not required)
• Take pride in your work and thrive in meritocratic environments

Compensation and Benefits

$180,000 - $600,000 USD

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

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Our team is small, highly motivated, and focused on engineering excellence. We operate with a flat organisational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence.

Responsibilities:

• Work on the most critical modelling challenges at any given time.
• Get clarity on your first project before an offer.

Basic Qualifications:

• Believe truth-seeking AI is the most important and challenging problem.
• Be obsessed about building incredibly useful models.
• Be a power user of AI models.
• Have previously trained models used by millions of people (not required).
• Take pride in your work and thrive in meritocratic environments.

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While experience in one or more of the following areas is a strong plus: large-scale model training, research in 3D computer vision.

You will collaborate closely with researchers, engineers, and product teams to bring advanced 3D modeling and machine learning techniques into real-world applications, ensuring that our technology remains at the forefront of visual innovation. This role involves significant hands-on research and engineering work, driving projects from conceptualization through to production deployment.

Key responsibilities include designing, implementing, and training large-scale diffusion models for generating 3D worlds, developing and experimenting with large-scale diffusion models to add novel control signals, adapting to target aesthetic preferences, or distilling for efficient inference, collaborating closely with research and product teams to understand and translate product requirements into effective technical roadmaps, contributing hands-on to all stages of model development including data curation, experimentation, evaluation, and deployment, continuously exploring and integrating cutting-edge research in diffusion and generative AI more broadly, acting as a key technical resource within the team, mentoring colleagues, and driving best practices in generative modeling and ML engineering.

Ideal candidate profile includes 3+ years of experience in generative modeling or applied ML roles, extensive experience with machine learning frameworks such as PyTorch or TensorFlow, especially in the context of diffusion models and other generative models, deep expertise in at least one area of generative modeling, strong history of publications or open-source contributions involving large-scale diffusion models, strong coding proficiency in Python and experience with GPU-accelerated computing, ability to engage effectively with researchers and cross-functional teams, clearly translating complex technical ideas into actionable tasks and outcomes, comfortable operating within a dynamic startup environment with high levels of ambiguity, ownership, and innovation.

Nice to have includes contributions to open-source projects in the fields of computer vision, graphics, or ML, familiarity with large-scale training infrastructure, experience integrating machine learning models into production environments, led or been involved with the development or training of large-scale, state-of-the-art generative models.

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The best generative models aren’t just a product of model architecture and compute, they are a product of the training data. The model output reflects someone’s obsession over what goes into the data, how it’s processed, and what gets thrown away. We’re looking for the person who does the obsessing and builds the tools to act on it at scale.

This isn’t a role where someone hands you a dataset and asks you to clean it. You will decide what data we need, figure out where to get it, build the processing and curation systems, and close the loop with model training to make sure it actually works.

Responsibilities:

• Discover, evaluate, and acquire training data
• Build data processing and curation systems
• Look at the actual data constantly
• Close the data → model → evaluation loop
• Deploy ML models for data enrichment
• Make systematic, documented decisions

Requirements:

• Strong software engineering fundamentals
• Deep experience with image and video data at scale
• Experience with distributed computing
• Experience using ML models as components
• A research-oriented approach to data decisions
• Familiarity with the model training lifecycle

Nice to Have:

• Familiarity with columnar and large-scale data storage formats and libraries
• Track record of independently discovering and integrating new data sources into a training pipeline
• Direct experience closing the data → model quality loop
• Strong visual intuition for data quality and diversity

What This Isn’t:

• Not infrastructure
• Not pure research
• Not a role where you wait for instructions

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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 company with teams distributed between France, USA, UK, Germany, and Singapore. We offer a comprehensive AI platform that meets enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.

Role Summary

Mistral AI is seeking Applied Scientists Interns and Research Engineers Interns to drive innovative research and collaborate with clients on complex research projects. You will develop SOTA models across different modalities such as text, image, and speech. By developing novel methods and research ideas, you will apply these models across a diverse set of use cases and domains.

Responsibilities

• Run pre-training, post-training, and deploy state-of-the-art models on clusters with thousands of GPUs. • Generate and curate data for pre-training and post-training, working on evaluations and making sure the model's performance beats expectations. • Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation, and deployment. • Collaborate with cross-functional teams to tackle complex use cases using agents and RAG pipelines. • Manage research projects and communications with client research teams.

About You

• You are fluent in English, and have excellent communication skills. You are at ease explaining complex technical concepts to both technical and non-technical audiences. • You're an expert with PyTorch or JAX. • You're not afraid of contributing to a big codebase and can find yourself around independently with little guidance. • You write clean, readable, high-performance, fault-tolerant Python code. • You don't need roadmaps: you just do. You don't need a manager: you just ship. • Low-ego, collaborative, and eager to learn. • You have a track record of success through personal projects, professional projects, or in academia.

Benefits

• Competitive salary • Food: Daily lunch vouchers • Sport: Monthly contribution to a Gympass subscription • Transportation: Monthly contribution to a mobility pass

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

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

Key Responsibilities:

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

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

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

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

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

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

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

Requirements:

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

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

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

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

Familiarity with Kubernetes/Slurm is a strong plus.

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

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

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

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

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

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

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

Preferred Qualifications:

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

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

Proficient coding skills are strongly recommended

Kubernetes know-how strongly recommended

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

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

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

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We are seeking a highly motivated and innovative Research Scientist to join our team in Bangalore, focused on advancing the state-of-the-art in autonomous agents through reinforcement learning and ML optimization methods.

As a Research Scientist at Google DeepMind, you will conduct cutting-edge research on large language models (LLMs), focusing on the development of more capable, robust autonomous agents.

Key Responsibilities:

• Design, implement and evaluate models, agents and software prototypes of large foundational models.
• Push the boundary of state of the art RL methods and machine learning optimization methods to build autonomous agents.
• Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing.
• Suggest and engage in team collaborations to meet ambitious research goals.
• Work with external collaborators and maintain relationships with relevant research labs and key individuals as appropriate.
• Work in collaboration with our Responsible AI teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity.

About You:

• You are a passionate and talented researcher with a strong foundation and a proven ability to conduct impactful research in AI.
• You have a collaborative mindset and are excited to work as part of a team to tackle ambitious research challenges.
• You are passionate about seeing your research translated into real-world products that improve the lives of users and are eager to work in an environment where research has a direct path to product impact.

Requirements:

• PhD in Computer Science, Artificial Intelligence, or a related field.
• Strong publication record in top-tier machine learning conferences or journals.
• Solid understanding of deep learning, natural language processing, computer vision, and/or speech processing.
• Experience with relevant ML frameworks such as JAX, TensorFlow, or PyTorch.

Preferred Qualifications:

• Experience with multimodal learning, large language models, and/or assistive AI agents.
• Experience with prompt engineering, few-shot learning, post-training techniques, and evaluations.
• Familiarity with large-scale model training and deployment.
• Strong programming skills in Python or similar languages.
• Excellent communication and collaboration skills.

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Responsibilities:

• Drive the development of AI features that drive impact
• Partner with Engineering to set strategy and priorities for teams and projects
• Define a vision and roadmap for AI-driven user experiences
• Build and maintain a strong understanding of AI technology in the payment industry
• Partner with cross-functional teams to improve features

Requirements:

• 5+ years of product management experience
• Proven track record shipping and iterating on AI features that drive impact
• Experience with Fintech or SaaS industry
• Experience working in a fast-paced, scrappy environment

Preferred skills:

• Experience with AI model training, evaluation, and iteration
• Ability to communicate clearly at different altitudes, including driving alignment with senior stakeholders
• An affinity for the fast-paced, changing environment of a start-up, a sense of humor, and get-it-done personality

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You'll be responsible for a full end-to-end slice of our product. From the idea on a whiteboard to something that customers use (and love), it's yours to drive.

Responsibilities

• Build and maintain a strong understanding of AI technology in the payment industry - its constraints, strengths and weaknesses in a fast evolving environment
• Define a vision and roadmap for AI driven user experiences, motivating model research and guiding product development with clear requirements
• Partner with a wide range of cross-functional partners across Product, Design, Engineering, and Data Science to improve a range of features
• Partner with Engineering to set strategy and priorities for teams and projects

Requirements

• 5+ years of product management experience
• Proven track record shipping and iterating on AI features that drive impact
• Experience with Fintech or SaaS industry
• Experience working in a fast-paced, scrappy environment

Benefits

• Health, dental, and vision coverage
• Paid time off and paid parental leave
• Opportunities for career growth and development
• Impact the experience of world-known clients

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Responsibilities:

Pioneer research and stay up-to-date with the latest advancements in AIGC and VLM, applying SOTA technologies and frameworks to enhance the quality and performance of ad content generation.

Optimize and scale high-performance, large-volume systems to reliably handle massive datasets and ensure high throughput.

Lead the data collection, model training, evaluation, and deployment of advanced image processing and generation algorithms.

Analyse system performance and identify opportunities based on data analysis and online experiments.

Collaborate effectively with cross-functional teams (e.g., product manager, engineering, research) to deliver high-quality, end-to-end solutions.

Qualifications:

Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

4+ years of industry experience with a focus on computer vision, image/video generation and editing.

Demonstrated leadership or significant contributions to the design, data, training of advanced AIGC models (e.g. diffusion/AR models and distillation, VAEs etc.).

Excellent design and problem-solving skills, with a proven ability to translate ambiguous problems into clear, implementable solutions.

Proactive communication skills, with the ability to collaborate effectively across algo, product, and engineer teams.

Preferred Qualifications:

Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

5+ years of industry experience with a focus on computer vision, image/video generation and editing.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role

Anthropic's sandboxing infrastructure enables Claude to safely execute code and interact with external systems. As we expand Claude's capabilities, the reliability, security, and developer experience of this infrastructure becomes increasingly critical. We're looking for an engineer to join the sandboxing team and help shape both the client-side library/API and the underlying infrastructure.

In this role, you'll combine deep infrastructure expertise with an obsession for developer experience. You'll help maintain and evolve a system that must be correct, performant, and intuitive to use. You'll work closely with internal teams to understand their needs, burn down errors and edge cases, and build a roadmap that anticipates where the product needs to go. This is a role for someone who finds satisfaction in both the craft of building reliable systems and the empathy required to serve developers and researchers well.

Responsibilities

• Contribute to the client library, API surface, and underlying infrastructure for Anthropic's sandboxing system, ensuring it is reliable, well-documented, and intuitive to use

• Drive down error rates and improve correctness through systematic debugging, monitoring, and proactive fixes

• Help develop and maintain a product roadmap for sandboxing capabilities, balancing immediate needs with long-term architectural improvements

• Partner closely with internal teams using the sandboxing system to understand their requirements, debug issues, and build tooling that serves their use cases

• Respond to incidents and production issues with urgency, conducting thorough root cause analysis and implementing preventive measures

• Build comprehensive testing, observability, and documentation to ensure the system meets a high quality bar

• Collaborate across the sandboxing team, flexing between client-side and infrastructure work as needed

You May Be a Good Fit If You

• Have 5+ years of software engineering experience, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs

• Obsess over developer experience—you've thought deeply about API design, error propagation, documentation, and the small details that make a library feel well-crafted

• Have experience operating complex distributed systems

• Bring a track record of systematically improving reliability—you've burned down error budgets, built monitoring, and driven issues to resolution

• Can develop and articulate a long-term vision for a product, translating user feedback and technical constraints into a coherent roadmap

• Are comfortable with ambiguity and can context-switch between reactive incident work and proactive product development

• Communicate clearly with both technical and non-technical stakeholders

Strong Candidates May Also Have

• Experience as a founder or early engineer at an infrastructure-focused startup, where you owned a product end-to-end

• Background in security, sandboxing, or isolation technologies (containers, VMs, seccomp, namespaces, etc.)

• Open-source contributions in the Python ecosystem

• Experience building developer tools, CLIs, or platforms used by other engineers

• History of working on incident response and on-call rotations for production systems

• Exposure to reinforcement learning or model training infrastructure

Representative Projects

These are examples of past work that would indicate a good fit—not a description of the role itself:

• Maintaining an open source SDK through multiple major version upgrades while minimizing breaking changes for users

• Leading an initiative to reduce P0 incidents by XX% through improved error handling, retries, and observability

• Building a developer platform at a startup from zero to product-market fit, iterating based on user feedback

• Embedding with an internal team for a quarter to deeply understand their workflows and shipping targeted improvements to a piece of infrastructure they rely on

• Developing a multi-quarter roadmap for a developer tools product, balancing user requests with technical debt reduction

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.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building can have a huge impact on society, and we want to make sure that the people building them are representative of the people they'll be serving.

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We're looking for Research Engineers to help us build the next generation of training environments for capable and safe agentic AI. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to research direction.

Responsibilities:

• Build the next generation of agentic environments
• Build rigorous evaluations that measure real capability
• Collaborate across research and infrastructure teams to ship environments into production training
• Debug and iterate rapidly across research and production ML stacks
• Contribute to research culture through technical discussions and collaborative problem-solving

You may be a good fit if you:

• Are highly impact-driven — you care about outcomes, not activity
• Operate with high agency
• Have good research taste or senior technical experience, demonstrating good judgment in identifying what actually matters in complex problem spaces
• Can balance research exploration with engineering implementation
• Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems
• Are comfortable with uncertainty and adapt quickly as the landscape shifts
• Have strong software engineering skills and can build robust infrastructure
• Enjoy pair programming (we love to pair!)

Strong candidates may also have one or more of the following:

• Have industry experience with large language model training, fine-tuning or evaluation
• Have industry experience building RL environments, simulation systems, or large-scale ML infrastructure
• Senior experience in a relevant technical field even if transitioning domains
• Deep expertise in sandboxing, containerization, VM infrastructure, or distributed systems
• Published influential work in relevant ML areas

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.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role:

Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems.

This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimisation, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow.

Responsibilities:

• Own critical aspects of our production pretraining pipeline, including model operations, performance optimisation, observability, and reliability
• Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure
• Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance
• Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams
• Build and maintain production logging, monitoring dashboards, and evaluation infrastructure
• Add new capabilities to the training codebase, such as long context support or novel architectures
• Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams
• Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned

You May Be a Good Fit If You:

• Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems
• Genuinely enjoy both research and engineering work—you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other
• Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure
• Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs
• Excel at debugging complex, ambiguous problems across multiple layers of the stack
• Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents
• Are passionate about the work itself and want to refine your craft as a research engineer
• Care about the societal impacts of AI and responsible scaling

Strong Candidates May Also Have:

• Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale
• Contributed to open-source LLM frameworks (e.g., open\_lm, llm-foundry, mesh-transformer-jax)
• Published research on model training, scaling laws, or ML systems
• Experience with production ML systems, observability tools, or evaluation infrastructure
• Background as a systems engineer, quant, or in other roles requiring both technical depth and operational excellence

What Makes This Role Unique:

This is not a typical research engineering role. The work is highly operational—you'll be deeply involved in keeping our production models training smoothly, which means being responsive to incidents, flexible about priorities, and comfortable with uncertainty. During launches, the team often works extended hours and may need to respond to issues on evenings and weekends.

However, this operational intensity comes with extraordinary learning opportunities. You'll gain hands-on experience with some of the largest, most sophisticated training runs in the industry. You'll work alongside world-class researchers and engineers, and the institutional knowledge you build will compound in ways that can't be easily transferred. For people who thrive on this type of work, it's uniquely rewarding.

We're building a close-knit team of people who genuinely care about doing excellent work together. If you're someone who wants to be part of training the models that will define the future of AI—and you're excited about the full reality of what that entails—we'd love to hear from you.

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.

We encourage you to apply even if you do not believe you meet every single qualification.

XML job scraping automation by YubHub

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Team

Our team is organised around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. Our team likes to think across the whole model stack. Currently the team is focused on improving models' abilities to use computers – as a laboratory for long horizon tasks and a key blocker to many scientific workflows.

About the role

As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimisation, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged.

Join us in our mission to develop advanced AI systems that are both powerful and beneficial for humanity.

Responsibilities:

• Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI
• Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery
• Scaling research ideas from prototype to production
• Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use
• Implement distributed training systems and performance optimisations to support large-scale model development

You may be a good fit if you:

• Have 8+ years of ML research experience
• Are familiar with large scale language model training, evaluation, and inference pipelines
• Enjoy obsessively iterating on immediate blockers towards longterm goals
• Thrive working collaboratively to solve problems
• Have expertise in performance optimisation and distributed computing systems
• Show strong problem-solving skills and ability to identify technical bottlenecks in complex systems
• Can translate research concepts into scalable engineering solutions
• Have a track record of shipping ML systems that tackle challenging multi-step reasoning problems

Strong candidates may also have:

• Expertise with performance optimisation for language model inference and training
• Experience with computer use automation and agentic AI systems
• A history working on reinforcement learning approaches for complex task completion
• Knowledge of containerisation technologies (Docker, Kubernetes) and cloud deployment at scale
• Demonstrated ability to work across multiple domains (language modelling, systems engineering, scientific computing)
• Have experience with VM/sandboxing/container deployment and large-scale data processing
• Experience working with large scale data problem solving and infrastructure
• Published research or practical experience in scientific AI applications or long-horizon reasoning

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.

We encourage you to apply even if you do not believe you meet every single qualification.** Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

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

How we're different

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

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As a Research Engineer on our team, you will work end to end across the whole model stack, identifying and addressing key infra blockers on the path to scientific AGI. Strong candidates should have familiarity with elements of language model training, evaluation, and inference and eagerness to quickly dive and get up to speed in areas they are not yet an expert on. This may include performance optimization, distributed systems, VM/sandboxing/container deployment, and large scale data pipelines.

Responsibilities:

• Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments
• Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities
• Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI.
• Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows
• Collaborate to translate experimental requirements into production-ready infrastructure
• Develop large scale data pipelines to handle advanced language model training requirements
• Optimize large scale training and inference pipelines for stable and efficient reinforcement learning

You may be a good fit if you:

• Have 6+ years of highly-relevant experience in infrastructure engineering with demonstrated expertise in large-scale distributed systems
• Are a strong communicator and enjoy working collaboratively
• Possess deep knowledge of performance optimization techniques and system architectures for high-throughput ML workloads
• Have experience with containerization technologies (Docker, Kubernetes) and orchestration at scale
• Have proven track record of building large-scale data pipelines and distributed storage systems
• Excel at diagnosing and resolving complex infrastructure challenges in production environments
• Can work effectively across the full ML stack from data pipelines to performance optimization
• Have experience collaborating with other researchers to scale experimental ideas
• Thrive in fast-paced environments and can rapidly iterate from experimentation to production

Strong candidates may also have:

• Experience with language model training infrastructure and distributed ML frameworks (PyTorch, JAX, etc.)
• Background in building infrastructure for AI research labs or large-scale ML organizations
• Knowledge of GPU/TPU architectures and language model inference optimization
• Experience with cloud platforms (AWS, GCP) at enterprise scale
• Familiarity with VM and container orchestration.
• Experience with workflow orchestration tools and experiment management systems
• History working with large scale reinforcement learning
• Comfort with large scale data pipelines (Beam, Spark, Dask, …)

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.

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

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

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale projects, and we're committed to making a positive impact on the world.

XML job scraping automation by YubHub

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role:

Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems.

This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow.

Responsibilities:

• Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability
• Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure
• Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance
• Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams
• Build and maintain production logging, monitoring dashboards, and evaluation infrastructure
• Add new capabilities to the training codebase, such as long context support or novel architectures
• Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams
• Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned

You May Be a Good Fit If You:

• Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems
• Genuinely enjoy both research and engineering work—you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other
• Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure
• Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs
• Excel at debugging complex, ambiguous problems across multiple layers of the stack
• Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents
• Are passionate about the work itself and want to refine your craft as a research engineer
• Care about the societal impacts of AI and responsible scaling

Strong Candidates May Also Have:

• Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale
• Contributed to open-source LLM frameworks (e.g., open\_lm, llm-foundry, mesh-transformer-jax)
• Published research on model training, scaling laws, or ML systems
• Experience with production ML systems, observability tools, or evaluation infrastructure
• Background as a systems engineer, quant, or in other roles requiring both technical depth and operational excellence

What Makes This Role Unique:

This is not a typical research engineering role. The work is highly operational—you'll be deeply involved in keeping our production models training smoothly, which means being responsive to incidents, flexible about priorities, and comfortable with uncertainty. During launches, the team often works extended hours and may need to respond to issues on evenings and weekends.

However, this operational intensity comes with extraordinary learning opportunities. You'll gain hands-on experience with some of the largest, most sophisticated training runs in the industry. You'll work alongside world-class researchers and engineers, and the institutional knowledge you build will compound in ways that can't be easily transferred. For people who thrive on this type of work, it's uniquely rewarding.

We're building a close-knit team of people who genuinely care about doing excellent work together. If you're someone who wants to be part of training the models that will define the future of AI—and you're excited about the full reality of what that entails—we'd love to hear from you.

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.

XML job scraping automation by YubHub

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role:

Agentic systems are becoming an increasingly important part of how AI is deployed. Over the last year, we’ve seen rapid adoption of Claude-powered agentic systems in spaces like coding, research, customer support, network security, and more. We believe this is just the beginning, and we expect Claude to be handling much more complex tasks end-to-end or in cooperation with a human user as time goes on. We have a team striving to make Claude an even more effective agent over longer time horizon tasks, and coordinate with groups of other agents at many different scales to accomplish large tasks. This team endeavors to maximize agent performance by solving challenges at whatever level is needed, whether it’s novel harness design, improved agent affordances and infrastructure, or finetuning.

Given that this is a nascent field, we ask that you share with us a project built on LLMs that showcases your skill at getting them to do complex tasks. Here are some example projects of interest: design of complex agents, quantitative experiments with prompting, constructing model benchmarks, synthetic data generation, or model finetuning. There is no preferred task; we just want to see what you can build. It’s fine if several people worked on it; simply share what part of it was your contribution. You can also include a short description of the process you used or any roadblocks you hit and how to deal with them, but this is not a requirement.

Responsibilities:

• Ideate, develop, and compare the performance of different agent harnesses (eg memory, context compression, communication architectures for agents)
• Design and implement rigorous quantitative benchmarks for large scale agentic tasks
• Assist with automated evaluation of Claude models and prompts across the training and product lifecycle
• Work with our product org to find solutions to our most vexing challenges applying agents to our products
• Help create and optimize data mixes for model training that maximize Claude’s performance or ease of use on agentic tasks

You may be a good fit if you:

• Have experience developing complex agentic systems using LLMs
• Have significant software engineering and ML experience
• Have spent time prompting and/or building products with language models
• Have good communication skills and an interest in working with other researchers on difficult tasks
• Have a passion for making powerful technology safe and societally beneficial
• Stay up-to-date and informed by taking an active interest in emerging research and industry trends.
• Enjoy pair programming (we love to pair!)

Strong candidates may also have experience with:

• Large-scale RL on language models
• Multi-agent systems

Representative projects:

• Design and build a novel agent harness that outperforms existing agents on coding or knowledge work benchmarks
• Design and build agent affordances that unlock new capabilities for internal use and deployed products
• Design and build a novel eval that measures how many agents interact in groups to solve problems
• Build a scaled model evaluation framework driven by model-based evaluation techniques.
• Build the prompting and model orchestration for a production application backed by a language model
• Finetune Claude to maximize its performance using a particular set of agent tools or harness

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.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you’re interested in this work. We think AI systems like the ones we’re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

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

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About the Team

OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort.

The Human Data engineering team creates the systems that enable scalable, high-quality human feedback. These systems are essential to how OpenAI trains and improves its most advanced models. Engineers on this team collaborate closely with world-class researchers to bring alignment techniques to life — from experimental ideas to production-ready feedback loops.

About the Role

We’re looking for software engineers to join the Human Data team and build the platforms, prototypes, tools, and infrastructure that power how our AI models are trained, aligned, and evaluated. You’ll partner with researchers and cross-functional teams to bring alignment ideas to life, influence future model training, and shape how models interact with the real world.

We’re looking for people who are excited by technical ownership, enjoy working across the stack, and are eager to solve ambiguous problems in a high-impact, fast-paced environment.

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:

• Build and maintain robust full-stack systems for feedback collection, data labeling, and evaluation pipelines, while maintaining high levels of security.

• Translate experimental alignment research into scalable production infrastructure, including inference and model training stacks.

• Design and iterate on user-facing tools and backend services to support high-quality data workflows

• Partner with researchers, engineers, and program leads to shape feedback loops and model interaction paradigms

• Drive infrastructure improvements that enable faster iteration and scaling across OpenAI’s frontier models, from internal research tooling all the way to production ChatGPT.

You might thrive in this role if you:

• Have strong software engineering fundamentals and experience building production systems at scale

• Enjoy full-stack development with end-to-end ownership — from backend pipelines to user interfaces

• Are motivated by high-impact collaboration with research teams and solving novel, ambiguous problems

• Are excited to shape how AI systems learn from human preferences and reflect a broad range of human values

• Care deeply about inclusive tooling and building systems that enhance model safety, reliability, and usefulness

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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Location

San Francisco; New York City; Remote - US; Seattle

Employment Type

Full time

Location Type

Hybrid

Department

IT

Compensation

• San Francisco, Seattle or New York City $230K – $385K • Offers Equity
• Zone A $207K – $346.5K • Offers Equity
• Zone B $184K – $308K • 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(es) for eligible employees, and the following benefits.

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 or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
• 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.

About the Team

Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect our model weights, customer data, and critical systems across multiple cloud environments. We partner with teams across OpenAI—Applied Engineering, Research, IT, and Security—to provide a secure and scalable platform for permissioning, orchestration, and innovative AI research.

About the Role

As a Software Engineer on the Identity Infrastructure Engineering team, you’ll be instrumental in creating, deploying, and operating foundational security tools and infrastructure. You will work with a broad range of technologies to support multi-cloud deployments, ensuring that researchers and engineers can safely build, test, and scale transformative AI systems. The role requires a balance of strong technical depth, cross-functional collaboration, and a passion for embedding secure-by-default principles into every layer of our stack.

Responsibilities

• Build new features for our IAM platform that seamlessly integrate with evolving cloud services, enabling teams to work efficiently while adhering to security best practices.
• Drive security innovation by designing tools, processes, and architectures that protect data at scale and reinforce a secure development culture across the organization.
• Collaborate cross-functionally with researchers, engineers, and compliance teams to address security requirements for multi-cloud deployments, large-scale model training, and emerging AI use cases.
• Implement and refine access policies that strike the right balance between enabling rapid experimentation and protecting high-value assets, including model weights and customer data.
• Troubleshoot complex identity or access issues across distributed systems, ensuring minimal downtime and a safe environment for AI research and product teams.

Requirements

• A background in building secure systems—from core IAM services to orchestration layers that manage credentials, roles, or policies at scale.
• Proficiency in programming languages such as Python, Go, or similar, with a track record of writing high-quality, maintainable code.
• Experience with modern cloud infrastructure (AWS, Azure, GCP) and familiarity with industry-standard security protocols (OAuth, SAML, OpenID Connect) and authentication/authorization patterns.
• A security-focused mindset, with knowledge of threat modeling, risk assessment, and the ability to embed security features throughout the software development lifecycle.

Nice to Have

• Experience with containerization (Docker, Kubernetes) and orchestration tools (e.g., Terraform, Ansible).
• Familiarity with CI/CD pipelines and automated testing frameworks.
• Knowledge of machine learning and AI concepts, including model training, deployment, and security.
• Experience with cloud security services (e.g., AWS IAM, Azure Active Directory).
• Familiarity with DevOps practices and tools (e.g., Jenkins, GitLab).

What You’ll Get

• Competitive salary and equity package
• Comprehensive benefits package, including medical, dental, and vision insurance
• 401(k) retirement plan with employer match
• Paid parental leave and medical/caregiver leave
• Flexible PTO and paid holidays
• Professional development opportunities
• Collaborative and dynamic work environment

How to Apply

If you’re passionate about building secure systems and contributing to the development of cutting-edge AI technology, we encourage you to apply for this exciting opportunity. Please submit your resume, cover letter, and any relevant work samples or projects you’d like to share. We can’t wait to hear from you!

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Location

San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $347K – $490K • 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(es) for eligible employees, and the following 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 or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• 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

The Applied team safely brings OpenAI's technology to the world. Our team launched ChatGPT, Advanced Voice Mode, Deep Research, and many other products, supporting scalable infrastructure and driving safe, responsible deployment. Our customers rely on our APIs to build transformative products, while we ensure responsible usage and platform integrity.

The Integrity team, within Applied Engineering, safeguards our platform by proactively identifying misuse, preventing abuse, and protecting users. We're seeking an experienced, hands-on Engineering Manager (Web Safety) to shape the future direction, architect advanced system protections, and lead a focused team of senior Machine Learning Engineers (MLEs).

In this role, you will:

• Architect and build next-generation system protections, directly contributing through hands-on design, model training, and deployment strategies.

• Lead and manage a small, senior team of Machine Learning Engineers, empowering them with clear direction and autonomy.

• Collaborate closely with Research, Safety, Product, and Policy teams to leverage existing tools and drive cutting-edge advancements.

• Utilize state-of-the-art models to detect and prevent problematic content effectively.

• Establish robust evaluation frameworks and metrics, clearly measuring progress and identifying areas for improvement.

• Support your team's professional growth and maintain high performance through mentorship and clear career progression.

You might thrive in this role if you:

• Bring extensive hands-on experience managing machine learning teams, ideally in web safety, content integrity, or related domains.

• Have successfully trained, fine-tuned, or distilled LLMs and traditional ML models to solve real-world business problems.

• Enjoy being deeply involved technically—actively designing solutions, training models, and guiding deployment processes alongside your team.

• Excel at collaborating across teams to integrate existing tools and thoughtfully architect new solutions.

• Possess strong emotional intelligence, empathy, and the ability to effectively connect with colleagues.

• Embrace ambiguity and rapidly changing circumstances as opportunities to create clarity, structure, and impactful solutions.

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

Early Career

ID: 5825

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.

We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.

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.

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency, and acumen in making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum, including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling, and machine learning. Aligned and partnered with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and craft the product roadmap, and prioritize, build data products, and measure impact on our community of players and developers.

WHY GENERATIVE AI?

Our team’s mission is to enable Roblox Creators to bring GenAI capabilities to millions of users. We drive this innovation with a core commitment to safety, responsibility, and quality.

As a Data Scientist, you will play a critical role in evaluation and optimization for user-facing GenAI systems (such as text, image, video, 3D, 4D). You will define how we measure safety, responsibility, quality, and efficiency. You will combine annotation analysis, design of experiments, causal inference, model-based evaluation methods (such as LLM-as-a-judge), optimization algorithm, and AI models to drive product decisions and model improvements.

You Will:

• Develop Evaluation Frameworks: Design and operationalize rigorous evaluation systems for either GenAI features (text, image, video, 3D, 4D). This includes eval experiment design, dataset design, label reliability analysis, and implementing and finetuning LLM-as-judge methods.

• Run Rigorous Experiments: Conduct online experiments (A/B tests) and causal inference to quantify the impact of GenAI features. You will identify opportunities, measure lift, and ensure statistical rigor.

• Define Success Metrics: Partner with cross-functional teams to define leading/lagging indicators for GenAI feature user satisfaction, business success, and safety.

• Build Automated Systems: Research and apply state-of-the-art methodologies to build reproducible evaluation tooling that lift rigor and efficiency across the company.

• Conduct Applied Research at the Frontier: Maintain an active pulse on the intersection of Gen AI and Data Science. You will innovate on methodology and techniques to solve unique business challenges while contributing to the broader field in the technical community.

You Have:

• Possess or pursuing a PhD or equivalent in Statistics, Economics, Computer Science, Applied Math, Physics, Engineering, or a related quantitative field.

• Technical Proficiency: Strong proficiency in SQL (Hive/Spark) for manipulating large datasets and scripting languages (Python or R) for analysis and modeling.

• Experimentation and Causal Inference: A solid grounding in experimentation, causal inference, and statistical analysis, including test design and metric design for feature impact.

• Problem Solving: A demonstrated track record of framing ambiguous problems, designing analytical approaches, and solving open-ended data science problems that drive business impact.

• Learning Agility: Ability to effectively and responsibly use AI tools to enhance productivity and a passion for continuously improving methods in a fast-evolving field.

• GenAI Familiarity: Familiarity with GenAI models and safety/quality evaluation methods. Expertise in the model training lifecycle is a plus (e.g., fine-tuning, RLHF, or synthetic data generation).

• Applied Research Background: A track record of applied research or publications in relevant technical fields is highly valued.

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

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

$185,860—$221,380 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 Applied Scientist at their Beijing office. This role sits at the heart of semantic search across Microsoft, powering the leading embedding models that generate the core vector representations and help on all Bing index content across web content, fresh, multimedia, ads and impact on multiple stacks from retrieval to ranking.

About the Role

The Full Body Vectorization (FBV) Team is the engine powering semantic search across Microsoft. We own and operate the leading embedding models that generate the core vector representations and help on all Bing index content across web content, fresh, multimedia, ads and impact on multiple stacks from retrieval to ranking. We are now building Next-Generation Search Engine and Grounding system to lead the technical wave and improve the quality of Search, Copilot and all kinds of tools benefit from AI. As an Applied Scientist, you will apply state-of-the-art Research/ Industry Innovation s to benefit on Search/ Grounding quality with measurable business impact. You will explore big bets with mature thinking, ability to drive the direction from idea to the product ship on production. You will collaborate with product, algo and engineering partners across the world with clear communication to push the project move further.

Accountabilities

• Apply state-of-the-art Research/ Industry Innovation s to benefit on Search/ Grounding quality with measurable business impact.
• Explore big bets with mature thinking, ability to drive the direction from idea to the product ship on production.
• Collaborate with product, algo and engineering partners across the world with clear communication to push the project move further.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.

Technical skills:

• Prior experience with Research, Applied Science, Search / Recommedation or other solid experience on deep model training.
• Experience with common machine learning, deep learning frameworks and concepts, using use of LLMs, prompting.
• Experience in pytorch or tensorflow.

Personal attributes:

• Solid coding ability for online system maintain/ update and feature change.
• Be sensitive to data. Help review design/ experiments/ pipelines with your expertise.

Benefits

• Microsoft’s mission is to empower every person and every organization on the planet to achieve more.
• As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.
• Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week.

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Microsoft AI are looking for a talented Applied Scientist at their Suzhou office. This role sits at the heart of semantic search across Microsoft, powering the leading embedding models that generate the core vector representations and help on all Bing index content across web content, fresh, multimedia, ads and impact on multiple stacks from retrieval to ranking.

About the Role

The Full Body Vectorization (FBV) Team is the engine powering semantic search across Microsoft. We own and operate the leading embedding models that generate the core vector representations and help on all Bing index content across web content, fresh, multimedia, ads and impact on multiple stacks from retrieval to ranking. We are now building Next-Generation Search Engine and Grounding system to lead the technical wave and improve the quality of Search, Copilot and all kinds of tools benefit from AI.

Accountabilities

• Apply state-of-the-art Research/ Industry Innovation s to benefit on Search/ Grounding quality with measurable business impact.
• Explore big bets with mature thinking, ability to drive the direction from idea to the product ship on production.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.

Technical skills:

• Prior experience with Research, Applied Science, Search / Recommedation or other solid experience on deep model training.
• Experience with common machine learning, deep learning frameworks and concepts, using use of LLMs, prompting.
• Experience in pytorch or tensorflow.

Personal attributes:

• Solid coding ability for online system maintain/ update and feature change.
• Keep learning and can help build sharing team culture with discussion and ideas from innovations.

Benefits

• Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week.

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What you'll do

• Develop and implement computer vision algorithms for tasks such as object detection, recognition, tracking, segmentation, and image classification.
• Design and architect computer vision systems to meet specific requirements and objectives.

What you need

• Bachelor’s or master’s degree in computer science, Electrical Engineering, or a related field.
• Proven experience in developing and implementing computer vision algorithms and models.
• Proficiency in programming languages such as Python or C++.
• Strong understanding of image and video processing techniques and methodologies.
• Familiarity with computer vision libraries such as OpenCV.
• Experience with data collection, annotation, and preparation for model training.
• Ability to evaluate and optimize model performance using appropriate metrics and benchmarks.
• Experience integrating computer vision solutions into software systems or products.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.

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