The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.

Strong candidates may also have experience with:

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Load balancing, request routing, or traffic management systems
• LLM inference optimization, batching, and caching strategies
• Kubernetes and cloud infrastructure (AWS, GCP)
• Python or Rust

You may be a good fit if you:

• Have significant software engineering experience, particularly with distributed systems
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Want to learn more about machine learning systems and infrastructure
• Thrive in environments where technical excellence directly drives both business results and research breakthroughs
• Care about the societal impacts of your work

Representative projects across the org:

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• Supporting inference for new model architectures
• Analyzing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

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

The annual compensation range for this role is £225,000-£325,000 GBP.

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Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.

The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.

Strong candidates may also have experience with:

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Load balancing, request routing, or traffic management systems
• LLM inference optimization, batching, and caching strategies
• Kubernetes and cloud infrastructure (AWS, GCP)
• Python or Rust

You may be a good fit if you:

• Have significant software engineering experience, particularly with distributed systems
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Want to learn more about machine learning systems and infrastructure
• Thrive in environments where technical excellence directly drives both business results and research breakthroughs
• Care about the societal impacts of your work

Representative projects across the org:

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• Supporting inference for new model architectures
• Analyzing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

Annual compensation range for this role is €235,000-€295,000 EUR.

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

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

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

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

How we're different:

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

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

Come work with us!

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

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As a Senior Software Engineer, you will be responsible for designing, implementing, and deploying large-scale distributed systems, including intelligent request routing, fleet-wide orchestration, and load balancing. You will work closely with our research team to develop new inference features and integrate new AI accelerator platforms.

To succeed in this role, you should have significant software engineering experience, particularly with distributed systems, and be results-oriented with a bias towards flexibility and impact. You should also be able to pick up slack, even if it goes outside your job description, and thrive in environments where technical excellence directly drives both business results and research breakthroughs.

Responsibilities:

• Design and implement large-scale distributed systems, including intelligent request routing, fleet-wide orchestration, and load balancing
• Work closely with our research team to develop new inference features and integrate new AI accelerator platforms
• Collaborate with cross-functional teams to ensure seamless deployment and operation of our systems
• Analyze observability data to tune performance based on real-world production workloads
• Manage multi-region deployments and geographic routing for global customers

Requirements:

• Bachelor's degree or equivalent combination of education, training, and/or experience
• Significant software engineering experience, particularly with distributed systems
• Results-oriented with a bias towards flexibility and impact
• Ability to pick up slack, even if it goes outside your job description
• Thrives in environments where technical excellence directly drives both business results and research breakthroughs

Preferred Qualifications:

• Experience with Kubernetes and cloud infrastructure (AWS, GCP)
• Familiarity with machine learning systems and infrastructure
• Strong communication and collaboration skills

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

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

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

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

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Key Responsibilities:

• Build cutting-edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data-driven methods and leverage the unique properties of our data to improve candidate retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keep up with industry trends in recommendation systems

Requirements:

• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• End-to-end hands-on experience with building data processing pipelines, large-scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• Degree in computer science, machine learning, statistics, or related field

Nice to Have:

• M.S. or PhD in Machine Learning or related areas
• Publications at top ML conferences
• Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
• Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
• Expertise in scalable real-time systems that process stream data
• Passion for applied ML and the Pinterest product

Relocation Statement:

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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The AI SDK team is pushing to keep Temporal at the forefront of AI applications. Because the landscape is constantly changing, we engage heavily in prototyping to ensure that the abstractions we develop meet the needs of emerging applications. We also ensure that Temporal integrates well with leading AI frameworks and libraries.

As a Staff Software Engineer, you will:

• Work as a Software Engineer.
• Design and implement Temporal AI SDK features supporting a broad variety of frameworks and libraries.
• Develop a deep understanding of AI application development techniques, including emerging approaches and architectures.
• Work with multiple programming languages, primarily Python and TypeScript.
• Make extensive use of AI coding tools, especially to ensure quality across a large number of integrations.
• Take end-to-end ownership of new features, working with other teams to deliver exceptional reliability and a great developer experience.
• Serve as a domain expert on AI design patterns, collaborating with field staff to provide best-practices and canonical examples.
• Work directly with our developer community to debug issues that need expert attention, and get feedback on Temporal SDK features and APIs.
• Write public technical documentation describing Temporal concepts and APIs.
• Go the extra mile to support a customer in need, on the rare occasion that AI SDK engineering expertise is needed.
• Travel to meet your coworkers for a week once or twice a year.
• Attend the occasional developer conference to talk about how great Temporal is (optional).

You won't:

• Work as a Data Scientist, Data Analyst, Devops SWE, or SRE.
• Work in an office (unless you want to, but you'd be by yourself). Temporal is a fully-remote company.
• Commit code that's poorly-tested or works 'most of the time'. Temporal aspires to be 'Reliable as Gravity', and we expect our code to be the same.
• Work behind closed doors. The SDKs are open source,that means PRs and comments are open to the public, too.
• Sit in meetings all day. We mostly communicate in writing, and use meetings mainly for status updates and thorny issues that need input from the whole group.
• Wake up to pager alerts. We're extremely active in supporting our customers and the community, but we don't do 24/7 on-call.

You'll bring:

• Experience and passion for harnessing generative AI, particularly for agents and coding.
• A deep understanding of how to use AI to increase quality, not only to increase quantity.
• A sense of taste in code and software development practice. Your approach should be opinionated and thoughtful, but not dogmatic.
• A track record of open source software contributions, including contributions to 3rd party libraries.
• Fluency in multiple programming languages, and an affinity for learning new ones.
• Deep experience with concurrent programming,you should know how to use mutexes, atomics, and other concurrency primitives safely.
• Experience designing APIs and writing documentation for publicly-available libraries or modules.
• Strong technical communication skills,written and verbal,in English.
• BS or MS in Computer Science (or a closely-related degree), or equivalent work experience writing production-grade software.

Nice to have:

• Familiarity with Temporal's programming model (e.g. you've written an app on Temporal).
• Expedite building agents or other AI applications
• Background in machine learning, model training, data science, or machine learning systems.
• Experience contributing to the architecture and design of large-scale distributed systems.
• Graduate degree in Computer Science.

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We're looking for a Senior Machine Learning Engineer to join our Monetization team. As a key member of the team, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

Key responsibilities include:

• Building cutting-edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partnering closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search)
• Using data-driven methods and leveraging the unique properties of our data to improve candidate retrieval
• Working in a high-impact environment with quick experimentation and product launches
• Keeping up with industry trends in recommendation systems

Requirements:

• 2+ years of industry experience applying machine learning methods
• Degree in computer science, statistics, or related field; or equivalent experience
• End-to-end hands-on experience with building data processing pipelines, large-scale machine learning systems, and big data technologies
• Practical knowledge of large-scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems

Nice to have:

• M.S. or PhD in Machine Learning or related areas
• Publications at top ML conferences
• Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
• Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
• Expertise in scalable real-time systems that process stream data
• Passion for applied ML and the Pinterest product
• Background in computational advertising

Relocation Statement:

This position is not eligible for relocation assistance.

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Our internal events play a key role in helping to shape and amplify Google DeepMind's culture, enabling collaboration and celebrating key moments for the organisation at an important stage of our journey.

As an Events Manager, you will be embedded in the GenAI Unit and will focus on events and experiences for this groundbreaking team whose mission is to build state of the art models and accelerate intelligent experiences across Google's platforms and products.

You will partner with teams across Google DeepMind and Google to deliver a variety of events across the globe including Town Halls, Summits, hackathons, offsites and celebrations to drive collaboration, knowledge sharing and connection at scale.

Key responsibilities:

• Own and strategically develop the full suite of GenAI Unit events programs, from large scale team events to intimate team gatherings.

• Respond nimbly to briefs from stakeholders to create event experiences in support of specific objectives, often with short lead times.

• Adapt and innovate, bringing fresh and innovative approaches in an ever-changing environment.

• Manage end to end event delivery and execution of large scale 2500+person events as well as small activations (for example: team summits, leadership meetings, launch celebrations).

• Domestic and international travel for global events programs.

• Create detailed project plans and timelines, tracking workstreams and deliverables, and flagging and mitigating risks.

• Create detailed briefs (documents and presentations) for executive stakeholders.

• Build budgets, tracking spend and processing contracts and purchase orders.

• Consult and partner with teams within the GenAI unit and across Google DeepMind (Events & Experiences, Enterprise Engineering, Workplace, Comms, Marketing etc) coordinating cross functional working groups to deliver seamless experiences that meet the agreed objectives.

• Brief and collaborate with external agencies and internal Google vendor partners on venue, technical production and logistics requirements.

• Track and analyze agreed event metrics to assess success and to inform future event programs.

• Ensure all events are compliant with Google's health and safety, regulatory, and other governance policies, providing a secure and welcoming environment for all.

To set you up for success as an Events Manager at Google DeepMind, we look for the following skills and experience:

• Exceptional attention to detail.

• Exceptional end to end project management skills and proven experience managing high complexity events through the full lifecycle, including planning, budgeting, execution, and retrospectives.

• Ability to throttle. Experience and passion for leading both large scale 2000+ person events as well as smaller scale activations with varying scopes and audiences.

• Comfortable navigating change and ambiguity in a very fast paced and demanding environment.

• Natural problem solving skills with a wildly creative, innovative, and curious approach to the work.

Open to new ideas and learning opportunities, even when deadlines are nearing.

• Ability to simultaneously manage multiple events at different stages and meet all deadlines.

• Excellent relationship building skills. Values colleagues as partners and has a long term lens on cross-org relationships.

• Interest or experience in science and innovative technology, including in the field of artificial intelligence research or deployment of machine learning systems.

• Must work from the Mountain View office 3 days a week.

• Flexibility for both national and international travel, at times on short notice.

• Minimum 8 years of experience in events leadership at the scales and scopes mentioned.

• Ability and curiosity to use AI tools practically and effectively in your work, with a recognition and awareness of AI’s responsible use, risks, and limitations.

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Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.

As a Staff Software Engineer on our Inference team, you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary.

Strong candidates may also have experience with

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Load balancing, request routing, or traffic management systems
• LLM inference optimization, batching, and caching strategies
• Kubernetes and cloud infrastructure (AWS, GCP)
• Python or Rust

You may be a good fit if you

• Have significant software engineering experience, particularly with distributed systems
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Want to learn more about machine learning systems and infrastructure
• Thrive in environments where technical excellence directly drives both business results and research breakthroughs
• Care about the societal impacts of your work

Representative projects across the org

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• Supporting inference for new model architectures
• Analyzing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

Deadline to apply

None. Applications will be reviewed on a rolling basis.

Annual compensation range

The annual compensation range for this role is £325,000-£390,000 GBP.

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.

Why work with us?

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

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

Come work with us!

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

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About the Role:

Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.

The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.

Responsibilities:

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• Supporting inference for new model architectures
• Analyzing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

Requirements:

• Significant software engineering experience, particularly with distributed systems
• Results-oriented, with a bias towards flexibility and impact
• Ability to pick up slack, even if it goes outside your job description
• Willingness to learn more about machine learning systems and infrastructure
• Thrive in environments where technical excellence directly drives both business results and research breakthroughs
• Care about the societal impacts of your work

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

Note: The salary range for this role is €235,000-€295,000 EUR per year.

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Artificial intelligence will be one humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users.

The Role

As an Engineering Director, you will lead the Create strategy. Teams within Create focus on empowering users to generate and refine various forms of content, from visual media to generative music. The teams also work on developing robust content input and understanding capabilities to seamlessly integrate users' ideas.

In addition to these areas, you will work closely with Product Management, User Experience, and Data Science to improve these features and to build new LLM-forward capabilities into the Gemini App product. You will deploy capabilities that drive daily usage of the product.

To build out these features, each of your areas have a deep connection to Generative AI (Gen AI). You will partner closely with different Gen AI counterparts to quickly bring the latest and greatest model capabilities from Google DeepMind's Gen AI unit into the product.

Your core responsibilities will include:

• Define and execute the overall technical strategy for the Create area within Gemini App, aligning with the broader product outlook and driving daily usage.

• Lead and manage multiple engineering teams focused on features like content input and understanding, and content generation.

• Partner closely with Product Management, User Experience, and Data Science leads to define product roadmaps and deliver new LLM-forward capabilities.

• Drive the integration of GenAI model capabilities into Gemini App products.

• Foster a culture of innovation, collaboration, and rapid iteration within the engineering teams.

• Establish and track key performance indicators for the Create area, focusing on DAU for Gemini App.

• Manage cross-functional dependencies and collaborations with Gen AI, Workspace, Labs, and others as required to deliver great features.

• Ensure the scalability, reliability, and performance of Create-related features.

Candidate Qualifications

In order to set you up for success, we look for the following skills and experience:

• Bachelor's degree in Computer Science or Engineering, or equivalent practical experience.

• 15 years of experience in software engineering, building and working with systems in the technology organization.

• 7 years of experience managing teams of software engineers and managers of software engineers.

In addition, the following would be an advantage:

• Master's or PhD degree in Computer Science, or a related technical field.

• Experience incubating and scaling new product initiatives from conception (0 to 1) to broad adoption in a fast-paced or startup environment.

• Expertise and direct experience in the application and deployment of large-scale AI/Machine Learning systems, particularly in generative AI for consumer products.

Salary

The US base salary range for this full-time position is between $307,000 - $427,000 + bonus + equity + benefits.

Benefits

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law.

If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

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Join our Talent and Leadership Development team to architect and scale flagship experiences that empower thousands of Bricksters worldwide. This is an opportunity to help redefine how development works in the era of AI , moving beyond workshops and courses toward embedded, continuous, and agent-supported learning.

Our team is organized around four core pillars that support every stage of the employee and leadership journey:

New Bricksters

We design and deliver a high-impact new hire orientation experience that ensures new joiners are engaged, connected to our culture, and equipped with the foundational knowledge needed to succeed.

Leaders

We equip leaders at all levels with the skills, mindsets, and frameworks needed to accelerate performance. This includes our flagship annual leadership conference - Leadershift.

High-Potential Talent

We run bespoke programs to support our high-potential talent to advance their careers and prepare them for wider leadership roles.

All Bricksters (Career & Growth)

We enable every Brickster to grow their career at Databricks through programs focused on career navigation and long-term growth.

The Impact You'll Have

• Own and scale one or more flagship talent development programs (e.g., career development, manager enablement, onboarding, or top talent acceleration).
• Design and implement AI-enabled learning experiences, including copilots, assistants, mentoring networks, and personalized learning pathways.
• Evolve programs from event-based learning to continuous, embedded development in the flow of work.
• Partner with HR, business leaders, and technical teams to translate business problems into scalable development solutions.
• Facilitate global programs across functions and regions (e.g., onboarding, leadership development).
• Build and experiment with new approaches to agentic learning , using AI agents, automation, and knowledge systems to support employees, managers, and leaders in real time.
• Leverage data, experimentation, and analytics to understand skills gaps, adoption, and business impact.
• Measure program effectiveness and continuously iterate using product and growth-mindset practices (pilots, testing, and iteration).

About You

• Bachelor's degree (or equivalent experience) and 5+ years owning global learning, talent, or people programs in fast-paced or scaling organizations.
• Experience building scalable programs (onboarding, manager development, leadership development, or talent acceleration) , not just facilitating workshops.
• Strong systems thinker: you design processes and experiences that work for thousands of employees, not dozens.
• Demonstrated curiosity and practical use of AI tools (e.g., copilots, knowledge assistants, automation workflows, personalization, or analytics) to improve employee or learning experiences.
• Comfortable experimenting and prototyping new solutions with limited resources.
• Highly analytical: you use data to prioritize problems, evaluate effectiveness, and drive adoption.
• Strong stakeholder management and ability to influence senior leaders.
• Clear communicator who can translate business needs into practical, scalable development solutions.
• Experience in technology or high-growth environments strongly preferred.

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As a Member of Technical Staff at xAI, you will build frameworks to improve the reasoning capability, build distributed reinforcement learning systems, techniques for inference time compute (e.g. tree search and planning), and develop environments for agents.

You will get exposure and will be expected to solve and take ownership of components across the entire stack.

Responsibilities

• Build robust and scalable distributed RL systems.
• Optimise frameworks to enable complex inference-time reasoning.
• Develop environments and harnesses for agents.

Basic Qualifications

• Experienced with large-scale reinforcement learning systems.
• Designing and implementing distributed systems.
• Keeping up with state-of-the-art RL and inference time compute algorithms.

Interview Process

After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 15 minute interview (“phone interview”) during which a member of our team will ask some basic questions. If you clear the initial phone interview, you will enter the main process, which consists of four technical interviews:

• Coding assessment in a language of your choice.
• Systems hands-on: Demonstrate practical skills in a live problem-solving session.
• Project deep-dive: Present your past exceptional work to a small audience.
• Meet and greet with the wider team.

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Artificial intelligence will be one humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users.

We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

The Role:

As an Engineering Director, you will lead the Create strategy. Teams within Create focus on empowering users to generate and refine various forms of content, from visual media to generative music. The teams also work on developing robust content input and understanding capabilities to seamlessly integrate users' ideas. In addition to these areas, you will work closely with Product Management, User Experience, and Data Science to improve these features and to build new LLM-forward capabilities into the Gemini App product.

You will deploy capabilities that drive daily usage of the product. To build out these features, each of your areas have a deep connection to Generative AI (Gen AI). You will partner closely with different Gen AI counterparts to quickly bring the latest and greatest model capabilities from Google DeepMind's Gen AI unit into the product.

Your core responsibilities will include:

• Define and execute the overall technical strategy for the Create area within Gemini App, aligning with the broader product outlook and driving daily usage.

• Lead and manage multiple engineering teams focused on features like content input and understanding, and content generation.

• Partner closely with Product Management, User Experience, and Data Science leads to define product roadmaps and deliver new LLM-forward capabilities.

• Drive the integration of GenAI model capabilities into Gemini App products.

• Foster a culture of innovation, collaboration, and rapid iteration within the engineering teams.

• Establish and track key performance indicators for the Create area, focusing on DAU for Gemini App.

• Manage cross-functional dependencies and collaborations with Gen AI, Workspace, Labs, and others as required to deliver great features.

• Ensure the scalability, reliability, and performance of Create-related features.

Candidate Qualifications

In order to set you up for success, we look for the following skills and experience:

• Bachelor's degree in Computer Science or Engineering, or equivalent practical experience.

• 15 years of experience in software engineering, building and working with systems in the technology organization.

• 7 years of experience managing teams of software engineers and managers of software engineers.

In addition, the following would be an advantage:

• Master's or PhD degree in Computer Science, or a related technical field.

• Experience incubating and scaling new product initiatives from conception (0 to 1) to broad adoption in a fast-paced or startup environment.

• Expertise and direct experience in the application and deployment of large-scale AI/Machine Learning systems, particularly in generative AI for consumer products.

• The US base salary range for this full-time position is between $307,000 - $427,000 + bonus + equity + benefits.

Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.

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We are seeking a highly skilled Technical Support Engineer to provide high-quality support and service to our Customer base and Internal teams.

As a Technical Support Engineer, you will play a critical role in providing advanced support directly to our Customers, and collaborating with engineering and Sales teams to enhance our products and services.

Responsibilities:

• Resolve technical issues and provide advanced support directly to customers, including support for fal's platform (APIs, UI issues, and troubleshooting errors).
• Support users across multiple products via email, chat, and Slack.
• Troubleshoot integration issues, including authentication problems (OAuth, API keys), HTTP errors, malformed requests, rate limits, and API misconfigurations.
• Analyze API logs, error messages, and request/response payloads to identify root causes.
• Manage support tickets by responding within SLA timeframes, escalating complex issues appropriately, and maintaining detailed case records.
• Reproduce, escalate, and document bugs or edge cases in collaboration with engineering.
• Provide structured feedback to engineering teams regarding platform reliability, performance bottlenecks, and customer-reported issues, serving as an internal advocate for customer pain points and product improvement.
• Assist with testing and validation of new features, releases, and infrastructure changes before production deployment.
• Write and maintain technical content, including use case guides, how-to examples, FAQs, solutions for common errors, and documentation of issues and resolutions for the knowledge base.
• Improve developer documentation to make integration as self-serve as possible.

What You Bring:

• Strong analytical thinking, technical problem-solving skills, and a systematic approach to troubleshooting technical issues across web platforms, cloud environments, and enterprise software.
• Experience supporting and troubleshooting REST APIs and backend services, including working directly with REST APIs and authentication flows (OAuth2, API keys).
• Experience using monitoring, logging, and observability tools to support production systems.
• Familiarity with AI platforms, machine learning systems, or data-intensive applications.
• Excellent written and verbal communication and interpersonal skills, with the ability to clearly and empathetically explain complex technical concepts to both technical and non-technical stakeholders/users in English.
• Experience providing technical support with a customer-first mindset, demonstrating patience, empathy, and a focus on user success.
• Strong technical writing abilities with experience creating and maintaining user guides, FAQs, and troubleshooting documentation.
• Demonstrated ability to prioritize effectively, respond quickly to critical issues with a sense of urgency, and maintain composure under pressure.
• Ability to work independently and collaboratively, handling multiple concurrent support cases while maintaining quality and meeting response time commitments.
• Self-starter who can identify process improvements and proactively address recurring issues (Initiative).
• Familiarity with tools such as Slack, Linear, Notion, and GitHub.
• Familiarity with authentication protocols like REST APIs, OAuth2, JWT, and API key auth.

Why fal:

At fal, you'll join a rapidly scaling company defining how AI moves from experimentation to production. This is an opportunity to shape the future of enterprise AI adoption while building deep relationships with customers who are transforming their industries through intelligent technology.

What we offer at fal:

• Interesting and challenging work
• Competitive salary and equity
• A lot of learning and growth opportunities
• Regular team events and offsites

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Your work will ensure that every feature we launch is grounded in data-driven insight and meaningfully strengthens the connection between more than 700 million listeners and the creators they love.

Responsibilities:

• Own analytical projects end-to-end, from hypothesis generation and data exploration to recommendations for product leadership
• Develop and own success metrics for generative music features and systems
• Design and analyze A/B tests and causal studies to evaluate product and model impact
• Perform exploratory analyses to uncover opportunities that improve experiences for listeners and artists
• Build scalable dashboards to monitor feature health and ecosystem impact
• Design and run evaluations for generative music systems, assessing risks and opportunities across prompts, outputs, and quality
• Collaborate with Product, Design, Research, Marketing, and Engineering to translate insights into product requirements
• Partner closely with Engineers and AI Researchers to integrate evaluation signals into model development workflows
• Communicate complex findings through clear, actionable narratives that inform product strategy and roadmap decisions

Who You Are:

• You have a degree in Computer Science, Statistics, Economics, Operations Research, quantitative social science, or a related field (or equivalent experience)
• You bring 4+ years of experience as a Data Scientist influencing product decisions through data
• You're highly proficient in SQL and Python and comfortable working with large-scale datasets
• You use AI-powered tools (e.g., Cursor, Copilot) to accelerate analysis and workflows
• You have strong product intuition and a results-focused perspective, you seek the 'why' behind the data
• You have experience with A/B testing, causal inference and advanced statistical methods, and exercise strong judgment in methodological choices
• You understand machine learning systems and can evaluate models beyond offline metrics, applying human judgment to quality and impact
• You thrive in ambiguous, zero-to-one environments and enjoy defining metrics & opportunities for entirely new product categories
• You're motivated by creating real value for music fans and music creators

Where You'll Be:

• We offer you the flexibility to work where you work best! For this role, you can be within the EST timezone region as long as we have a work location.
• This team operates within the Eastern Standard time zone for collaboration

Additional Information: The United States base range for this position is $110,018 - $157,169 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave.

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The ideal candidate will bring strong experience in Cornerstone administration and demonstrate high learning agility to quickly master new tools and technologies. This position plays a key role in supporting the organization's learning strategy by ensuring systems run smoothly and efficiently.

What You'll Do

• Serve as the primary administrator and subject matter expert for Cornerstone on Demand and other learning systems
• Manage system configurations, updates, integrations, and user support
• Ensure data accuracy, reporting, and system compliance
• Support the implementation and optimization of new AI-driven learning solutions
• Troubleshoot technical issues and provide timely resolution
• Partner with internal stakeholders to improve learning processes and user experience
• Maintain documentation, workflows, and system best practices
• Provide guidance and training to users when necessary

Requirements

Experience

• Experience in learning systems administration
• Strong experience with Cornerstone on Demand
• Experience working with Microsoft Office Suite

• Fluent English (required)

Skills & Capabilities

• Advanced attention to detail
• Intermediate written and verbal communication skills
• Customer-focused mindset
• Intermediate decision-making and problem-solving skills
• Strong learning agility and ability to quickly adapt to new technologies

Benefits

This position comes with a competitive compensation and benefits package:

1. Competitive salary and performance-based bonuses
2. Comprehensive benefits package
3. Career development and training opportunities
4. Flexible work arrangements (remote and/or office-based)
5. Dynamic and inclusive work culture within a globally renowned group
6. Private Health Insurance
7. Pension Plan
8. Paid Time Off
9. Training & Development

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We are seeking experienced leaders to join our growing Learning Transformation Practice at Senior Principal level. You will play a pivotal role in shaping, selling, and delivering large-scale learning transformation programmes that help global organisations future-proof their workforce.

As a Senior Principal, you’ll combine strategic advisory, commercial acumen, and delivery excellence to lead complex, multi-tower engagements that transform how enterprises learn, reskill, and perform.

Key Responsibilities

Sales & Growth Leadership

• Lead end-to-end pursuit and sales cycles for large, complex learning transformation deals.
• Shape solution blueprints, proposals, and client narratives that position Infosys as a trusted learning transformation partner.
• Build relationships with Learning and Talent client stakeholders, and business leaders to identify opportunities for learning innovation and managed growth.
• Collaborate across Infosys Consulting, Infosys Ltd, and BPM to integrate learning into broader technology, HR, and business transformation programmes.
• Contribute to market visibility through thought leadership and GTM collateral and campaigns.

Programme Delivery & Leadership

• Oversee design and delivery of complex learning programmes, ensuring high standards of quality, timeliness, and measurable impact.
• Act as the executive sponsor and escalation point for delivery teams, ensuring client satisfaction and programme success.
• Lead globally distributed teams, leveraging offshore delivery and vendor partnerships effectively.
• Drive governance, risk management, and continuous improvement across delivery portfolios.
• Manage, lead design and development capability when operating at scale production. Overseeing this talent and ensuring we are pushing boundaries and staying relevant and competitive with regards to design and development standards.

Strategy & Innovation

• Bring a forward-looking perspective on learning and skills transformation—AI in learning, data-driven skills intelligence, and the shift toward Learning-as-a-Service.
• Develop thought leadership and frameworks that strengthen Infosys’ market presence and value proposition.
• Build and nurture partnerships across the learning technology ecosystem (LXPs, LMS, Skills Intelligence vendors etc.).

People and practice management:

• Seeks to give team members stretching opportunities while providing support and ensuring quality and operational excellence
• Lead collaborative sessions to help drive innovation and foster a culture of learning in the team
• Define, implement and manage best practice development processes that enable the team to deliver high quality, scalable solutions. Proactively lead on improving existing processes / approaches where required
• Encourages development of team members though formal and informal coaching
• Gives authentic and constructive feedback
• Reinforces our values, through day-to-day behaviour and change disrespectful behaviour
• Acts as a team player, with an ability to integrate with new teams quickly

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The ideal candidate will bring strong experience in Cornerstone administration and demonstrate high learning agility to quickly master new tools and technologies. This position plays a key role in supporting the organization's learning strategy by ensuring systems run smoothly and efficiently.

What You'll Do

• Serve as the primary administrator and subject matter expert for Cornerstone on Demand and other learning systems
• Manage system configurations, updates, integrations, and user support
• Ensure data accuracy, reporting, and system compliance
• Support the implementation and optimization of new AI-driven learning solutions
• Troubleshoot technical issues and provide timely resolution
• Partner with internal stakeholders to improve learning processes and user experience
• Maintain documentation, workflows, and system best practices
• Provide guidance and training to users when necessary

Requirements

Experience

• Experience in learning systems administration
• Strong experience with Cornerstone on Demand
• Experience working with Microsoft Office Suite

• Fluent English (required)

Skills & Capabilities

• Advanced attention to detail
• Intermediate written and verbal communication skills
• Customer-focused mindset
• Intermediate decision-making and problem-solving skills
• Strong learning agility and ability to quickly adapt to new technologies

Benefits

This position comes with a competitive compensation and benefits package:

1. Competitive salary and performance-based bonuses
2. Comprehensive benefits package
3. Career development and training opportunities
4. Flexible work arrangements (remote and/or office-based)
5. Dynamic and inclusive work culture within a globally renowned group
6. Private Health Insurance
7. Pension Plan
8. Paid Time Off
9. Training & Development

XML job scraping automation by YubHub

The ideal candidate will bring strong experience in Cornerstone administration and demonstrate high learning agility to quickly master new tools and technologies. This position plays a key role in supporting the organization's learning strategy by ensuring systems run smoothly and efficiently.

What You'll Do

• Serve as the primary administrator and subject matter expert for Cornerstone on Demand and other learning systems
• Manage system configurations, updates, integrations, and user support
• Ensure data accuracy, reporting, and system compliance
• Support the implementation and optimization of new AI-driven learning solutions
• Troubleshoot technical issues and provide timely resolution
• Partner with internal stakeholders to improve learning processes and user experience
• Maintain documentation, workflows, and system best practices
• Provide guidance and training to users when necessary

Requirements

Experience

• Experience in learning systems administration
• Strong experience with Cornerstone on Demand
• Experience working with Microsoft Office Suite

• Fluent English (required)

Skills & Capabilities

• Advanced attention to detail
• Intermediate written and verbal communication skills
• Customer-focused mindset
• Intermediate decision-making and problem-solving skills
• Strong learning agility and ability to quickly adapt to new technologies

Benefits

This position comes with a competitive compensation and benefits package:

1. Competitive salary and performance-based bonuses
2. Comprehensive benefits package
3. Career development and training opportunities
4. Flexible work arrangements (remote and/or office-based)
5. Dynamic and inclusive work culture within a globally renowned group
6. Private Health Insurance
7. Pension Plan
8. Paid Time Off
9. Training & Development

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Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.

As a Staff Software Engineer on our Inference team, you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary.

Strong candidates may also have experience with

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Load balancing, request routing, or traffic management systems
• LLM inference optimization, batching, and caching strategies
• Kubernetes and cloud infrastructure (AWS, GCP)
• Python or Rust

You may be a good fit if you

• Have significant software engineering experience, particularly with distributed systems
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Want to learn more about machine learning systems and infrastructure
• Thrive in environments where technical excellence directly drives both business results and research breakthroughs
• Care about the societal impacts of your work

Representative projects across the org

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• Supporting inference for new model architectures
• Analyzing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

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

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 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

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Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.

The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.

You may be a good fit if you:

• Have significant software engineering experience, particularly with distributed systems
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning systems and infrastructure
• Thrive in environments where technical excellence directly drives both business results and research breakthroughs
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Load balancing, request routing, or traffic management systems
• LLM inference optimization, batching, and caching strategies
• Kubernetes and cloud infrastructure (AWS, GCP, Azure)
• Python or Rust

Representative projects:

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• Supporting inference for new model architectures
• Analyzing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

Deadline to apply:

None. Applications will be reviewed on a rolling basis.

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

The easiest way to understand our research directions is to read our recent research. This research co

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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

We're looking for a Software Engineer to work at the intersection of engineering and research on the Claude Code team. In this role, you'll collaborate directly with Anthropic's researchers to improve Claude’s coding capabilities through tooling, infrastructure, and evaluations. You'll build systems that help us understand where Claude Code excels and where it falls short—and then help close those gaps.

We're looking for engineers who can build robust, complex systems and who thrive in fast-paced, high-intensity environments. You'll take ambiguous problems and turn them into reliable infrastructure that accelerates our research.

Responsibilities

• Design and build eval systems that measure model capabilities across diverse coding tasks

• Build tooling and infrastructure that enables researchers to run experiments at scale

• Develop pipelines for data collection, processing, and analysis

• Create internal tools that improve researcher productivity and accelerate iteration cycles

• Serve as a bridge between product and research—bring strong product intuition to inform which capabilities matter most

• Work closely with researchers to translate research questions into engineering solutions

• Own systems end-to-end—from design through production reliability

You may be a good fit if you:

• Have built and owned complex systems—pipelines, infrastructure, or software that orchestrates many components and handles significant state and logic

• Thrive in high-intensity environments with fast iteration cycles

• Take full ownership of problems and drive them to completion independently

• Are a power user of agentic coding tools and have strong intuition about model capabilities and limitations

• Are comfortable diving into unfamiliar technical domains and figuring things out quickly

• Care deeply about correctness and reliability in the systems you build

• Are excited to work at the boundary between engineering and AI research

• Have at least 5 years of work experience

Strong candidates may also have experience with:

• Writing or maintaining eval/evaluation frameworks

• Reinforcement learning systems

• Working in high-performance, demanding environments—trading firms, quant funds, competitive research labs, or fast-moving startups where intensity is the norm

• Have research computing or scientific infrastructure background

• Have a strong quantitative foundation (math, physics, or related fields)

• Python and TypeScript

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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Location

San Francisco

Employment Type

Full time

Location Type

Hybrid

Department

People

Compensation

• $180K – $200K • 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

The People Programs team at OpenAI plays a pivotal role in creating an environment where every employee can thrive, grow, and contribute to our mission of ensuring that AGI benefits all of humanity. This expanding team develops and executes human-first strategies and programs that support our rapid growth, unique culture, and innovative spirit.

About the Role

We’re looking for a Manager Development Specialist to support manager development programming and coaching through strong program management and logistics at OpenAI.

This role owns the end-to-end operations and systems that enable the smooth, scalable delivery of manager development programs at OpenAI. It supports virtual and in-person programs, manages learning systems and data, and helps scale impact through coaching operations, facilitation support, and manager-facing resources—partnering closely with L&D, HRBPs, Workplace, and external partners.

Your Responsibilities:

• Program Operations and Facilitation: Drive day-to-day logistics for manager development programs, including scheduling, communications, stakeholder coordination, and smooth execution across virtual and in-person formats; regularly facilitate live sessions.

• Systems & Data: Own program setup, enrollment, and tracking in our Learning Management System (Sana) to support accurate measurement, reporting, and scalable delivery of learning programs.

• Instructional Design: Contribute to the design and iteration of manager development programs using adult learning principles to meet evolving business needs as the organization scales.

• Coaching Operations: Manage intake, onboarding, scheduling, and tracking for coaching participants, cohorts, and timelines in partnership with HRBPs, leaders, and external coaching providers.

• Learning Content & Enablement: Create, maintain, and scale manager-facing resources—including async training, job aids, templates, toolkits, and intranet content—to reinforce learning beyond live programs.

• Team Support: Provide ad hoc program, facilitation, and operational support to the team as needed.

We’re Seeking:

• 5+ years of experience designing, managing, facilitating, and scaling learning or manager development programs in a fast-paced, high-growth environment, with exposure to complex, multi-stakeholder initiatives.

• Strong end-to-end program ownership, including translating business needs into learning experiences, managing program workflows and systems, and ensuring high-quality delivery across manager and leadership programs.

• Experience leveraging learning systems and data (e.g., LMS platforms such as Sana or similar) to drive enrollment strategy, program sequencing, measurement, and continuous improvement—not just administration.

• Highly organized and detail-oriented, with the ability to balance strategic program thinking and hands-on execution, anticipate risks, and adapt programs in real time.

• Clear and influential communicator, comfortable partnering with L&D peers, HRBPs, leaders, facilitators, and external vendors to align on goals, expectations, and outcomes.

• Experience supporting and contributing to live learning experiences, including virtual and in-person sessions, with the ability to assist with facilitation, content iteration, or delivery as needed.

• Self-directed and proactive, with strong judgment and comfort operating in ambiguity while continuously improving program effectiveness and participant experience.

• Demonstrated experience supporting manager, leadership, or coaching programs—with an understanding of the unique challenges of manager capability-building—strongly preferred.

Workplace & Location

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San Francisco

Employment Type

Full time

Department

Research

Compensation

• $250K – $445K • 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 Alignment team at OpenAI is dedicated to ensuring that our AI systems are safe, trustworthy, and consistently aligned with human values, even as they scale in complexity and capability. Our work is at the cutting edge of AI research, focusing on developing methodologies that enable AI to robustly follow human intent across a wide range of scenarios, including those that are adversarial or high-stakes. We concentrate on the most pressing challenges, ensuring our work addresses areas where AI could have the most significant consequences. By focusing on risks that we can quantify and where our efforts can make a tangible difference, we aim to ensure that our models are ready for the complex, real-world environments in which they will be deployed.

The two pillars of our approach are: (1) harnessing improved capabilities into alignment, making sure that our alignment techniques improve, rather than break, as capabilities grow, and (2) centering humans by developing mechanisms and interfaces that enable humans to both express their intent and to effectively supervise and control AIs, even in highly complex situations.

About the Role

As a Research Engineer / Research Scientist on the Alignment team, you will be at the forefront of ensuring that our AI systems consistently follow human intent, even in complex and unpredictable scenarios. Your role will involve designing and implementing scalable solutions that ensure the alignment of AI as their capabilities grow and that integrate human oversight into AI decision-making.

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:

We are seeking research engineers and research scientists to help design and implement experiments for alignment research. Responsibilities may include:

• Develop and evaluate alignment capabilities that are subjective, context-dependent, and hard to measure.
• Design evaluations to reliably measure risks and alignment with human intent and values.
• Build tools and evaluations to study and test model robustness in different situations.
• Design experiments to understand laws for how alignment scales as a function of compute, data, lengths of context and action, as well as resources of adversaries.
• Design and evaluate new Human-AI-interaction paradigms and scalable oversight methods that redefine how humans interact with, understand, and supervise our models.
• Train model to be calibrated on correctness and risk.
• Designing novel approaches for using AI in alignment research

You might thrive in this role if you:

• Are a team player – willing to do a variety of tasks that move the team forward.
• Have a PhD or equivalent experience in research in computer science, computational science, data science, cognitive science, or similar fields.
• Have strong engineering skills, particularly in designing and optimizing large-scale machine learning systems(e.g., PyTorch).
• Have a deep understanding of the science behind alignment algorithms and techniques.
• Can develop data visualization or data collection interfaces (e.g., TypeScript, Python).
• Enjoy fast-paced, collaborative, and cutting-edge research environments.
• Want to focus on developing AI models that are trustworthy, safe, and reliable, especially in high-stakes scenarios.

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 of our team members, partners, and users.

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Research Engineer / Research Scientist - Foundations Retrieval IC

Location

San Francisco

Employment Type

Full time

Department

Research

Compensation

• $445K – $555K • 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 Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science.

About the Role

We’re looking for a researcher focused on our embedding retrieval efforts. You’ll work with a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods.

This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact.

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.

Responsibilities

• Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning.

• Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluating, and integrating embeddings into frontier models.

• Drive innovation in dense, sparse, and hybrid representation techniques, metric learning, and learning-to-retrieve systems.

• Collaborate closely with Pretraining, Inference, and other Research teams to integrate retrieval throughout the model lifecycle

• Contribute to OpenAI’s long-term vision of AI systems with memory and knowledge access capabilities rooted in learned representations.

You Might Thrive in This Role If You Have

• Proven experience leading high-performance teams of researchers or engineers in ML infrastructure or foundational research.

• Deep technical expertise in representation learning, embedding models, or vector retrieval systems.

• Familiarity with transformer-based LLMs and how embedding spaces can interact with language model objectives.

• Research experience in areas such as contrastive learning, supervised or unsupervised embedding learning, or metric learning.

• A track record of building or scaling large machine learning systems, particularly embedding pipelines in production or research contexts.

• A first-principles mindset for challenging assumptions about how retrieval and memory should work for large models.

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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Research Engineer, Retrieval & Search, Applied Engineering

Location

San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $293K – $585K • 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

We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API.

We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth.

About the Role

We are looking for an experienced Research Engineer to work on retrieval & search problems across our API and ChatGPT. As the AI landscape has evolved over the last few years, retrieval & search have emerged as key use cases for our models, and we are investing in ensuring that we can offer these search-based product experiences for our users. You will be at the center of our retrieval & search efforts as a company, and the progress you drive here will reach millions of end users.

In this role, you will:

• Work on retrieval & search algorithms and methodologies in close collaboration with our research team, including problems in such domains as document search, enterprise search, knowledge retrieval, and web-scale search.

• Deploy these search methodologies into production in both the API and ChatGPT to be used by millions of end users.

• Explore novel research topics in retrieval & search that may inform our product strategy in the medium and long term.

• Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world

You might thrive in this role if you:

• Have extensive prior experience building and maintaining production machine learning systems.

• Have prior experience working with vector databases, search indices, or other data stores for search and retrieval use cases

• Have prior experience building and iterating on internet-scale search systems

• Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done

• Have the ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines

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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Microsoft are looking for a talented Principal Software Engineer at their Beijing office. This role sits at the heart of AI infrastructure development, driving innovation in large-scale AI infrastructure. You will be instrumental in designing and implementing high-performance, massively scalable infrastructure required to deploy frontier LLM models.

About the Role

As a Principal Software Engineer on the AI Infrastructure team, you will be responsible for designing and implementing innovative system optimization solutions for internal LLM workloads. You will optimize LLM inference workloads through innovative kernel, algorithm, scheduling, and parallelization technologies. You will also continuously develop and maintain internal LLM inference infrastructure, discovering new LLM system optimization needs and innovations.

Accountabilities

• Keep up to date with and utilize the latest developments in LLM system optimization.
• Take the lead in designing innovative system optimization solutions for internal LLM workloads.
• Optimize LLM inference workloads through innovative kernel, algorithm, scheduling, and parallelization technologies.
• Continuously develop and maintain internal LLM inference infrastructure.
• Discover new LLM system optimization needs and innovations.

The Candidate we're looking for

Experience:

• A bachelor's degree or higher in computer science, engineering, or a related field, PhD is preferred.

Technical skills:

• Strong programming skills in Python and C/C++.
• 5+ years of experience in machine learning system development and optimization.

Personal attributes:

• A growth mindset and a passion for learning new things.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.
• Access to cutting-edge technology and resources.

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Microsoft are looking for a talented Senior Software Engineer at their Beijing office. This role sits at the heart of AI Infrastructure development, driving innovation in large-scale AI infrastructure. You will be instrumental in designing and implementing high-performance, massively scalable infrastructure required to deploy frontier LLM models.

About the Role

We are seeking brilliant and passionate engineers to work with us on the most interesting and challenging problems of AI Infrastructure development. As a Senior Software Engineer, you will be responsible for designing and implementing the high-performance, massively scalable infrastructure required to deploy frontier LLM models through innovative GPU kernel, compression, scheduling and parallelization optimizations.

Accountabilities

• Keep up to date with and utilize the latest developments in LLM system optimization.
• Discover/solve impactful technical problems, advance state-of-the-art LLM technologies, and translate ideas into production.
• Optimize LLM inference workloads through innovative kernel, algorithm, scheduling, and parallelization technologies.
• Continuously maintain internal LLM inference infrastructure.

The Candidate we're looking for

Experience:

• A bachelor's degree or higher in computer science, engineering, or a related field, PhD is preferred.

Technical skills:

• Strong programming skills in Python and C/C++.
• 2+ years of experience in machine learning system development and optimization.

Personal attributes:

• A growth mindset and a passion for learning new things.

Benefits

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

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Microsoft AI are looking for a talented Member of Technical Staff, Reinforcement Learning Systems to help build the world's most advanced reinforcement learning systems. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology.

About the Role

We are responsible for designing, developing, and operating the large-scale reinforcement learning systems that power several use cases across the Superintelligence team. We are looking for individuals who can contribute to cutting-edge research and help bridge the gap between cutting-edge research and robust, production-grade distributed systems. The ideal candidate has both distributed systems expertise and a scientific mindset and will be able to build complex and scalable systems from the ground up, identify and resolve performance bottlenecks, debug complex, cross-system issues with extremely high attention to detail, and contribute to solving scientific and research challenges.

Accountabilities

• Develop and tune the pretraining scalable software for Nvidia GB200 72NVL CX8 and AMD MIxxx architectures.
• Benchmark GB200 and AMD MIxxx GPU clusters.
• Gather data and insights to develop the pretraining compute roadmap.

The Candidate we're looking for

Experience:

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Technical skills:

• Experience with generative AI.
• Experience with distributed computing.

Personal attributes:

• A high degree of craftsmanship and pay close attention to details.
• Enjoy working in a fast-paced, design-driven, product development cycle.

Benefits

• Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.
• There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay

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What you'll do

You will dive into our rich datasets of conversational and agentic queries, leveraging cutting-edge training techniques to scale AI model performance. Through hands-on technical and organizational leadership, you will empower your team to develop SotA models for the use cases that matter most to our business and our users.

• Lead a team of researchers and engineers focused on training SotA models for Perplexity-relevant use cases, leveraging the latest supervised and reinforcement learning techniques.
• Drive research and engineering efforts to develop production models through advanced model training and alignment techniques, including RL, SFT, and other approaches.
• Become deeply familiar with the team’s technical stack, leading from the front through hands-on technical contributions.
• Own the data, training, and eval pipelines required to train and continuously improve LLM models.
• Design and iterate on model training and finetuning algorithms (e.g., preference-based methods, reinforcement learning from human or AI feedback) through an approach that balances scientific rigor and iteration velocity.
• Design evaluations and improve the production model training pipeline to reliably deliver models that lie on the Pareto frontier of speed and quality.
• Work closely with engineering teams to integrate in-house models into our product and rapidly iterate based on real-world usage.
• Manage day-to-day execution, project planning, and prioritization for the model training team to hit ambitious quality and performance goals.

What you need

• Proven experience with large-scale LLMs and Deep Learning systems.
• Strong Python and PyTorch skills; versatility across languages and frameworks is a plus.
• Experience leading or managing research or engineering teams working on large-scale AI model development, including driving complex projects from idea to production.
• Self-starter with a willingness to take ownership of tasks and navigate ambiguity in a fast-moving environment.
• Passion for tackling challenging problems in AI model quality, speed, safety, and reliability.
• 10+ years of technical experience, with at least 2 of those years as a manager and at least 4 of those years working on large-scale AI model development.

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What you'll do

Research & Development

• Post-train SOTA LLMs using the latest supervised and reinforcement learning techniques (SFT/DPO/GRPO)
• Leverage our rich query/answer dataset to scale model performance across Sonar, Deep Research, Comet, and Search products

What you need

• Proven experience with large-scale LLMs and Deep Learning systems

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