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Anthropic Fellows Program is designed to foster AI research and engineering talent by providing funding and mentorship to promising technical talent regardless of previous experience. Fellows primarily use external infrastructure such as open-source models and public APIs to work on empirical projects aligned with Anthropic's research priorities, aiming to produce public outputs like paper submissions. The program runs multiple cohorts yearly with rolling application reviews, expecting a start in January 2027 but flexible start dates can be requested. The program includes 4 months of full-time research, direct mentorship from Anthropic researchers, access to a shared workspace, connection to the AI safety and security research community, a weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD plus benefits varying by country, and funding for compute (~$15k/month) and other research expenses. The interview process involves an initial application and reference check, technical assessments and interviews, and a research discussion. Applicants are encouraged to apply even if they do not meet every qualification, with emphasis on diversity and inclusion. There are two main fellow tracks: ML Systems & Performance Fellows: - Mentors include Alwin Peng and Zygi Straznickas. - Projects may involve building CPU simulators for accelerator workloads, adding backends for accelerators on open source projects, building on-demand infrastructure, and creating complex synthetic data or environment pipelines. - Candidates should have strong software engineering skills, experience with complex ML systems, ability to balance research and engineering rigor, comfort with large-scale distributed systems and high-performance computing, experience with training or evaluating large language models, and skills in analyzing and debugging model training. - Fluency in Python and full-time availability are required. Reinforcement Learning Fellows: - Mentors include Ruhua Jiang, Kaidi Cao, Sunny Duan, David Brandfonbrener, Colt Steele, Dino Distefano, and Will Williams. - Projects may include building model-based tools to understand and improve AI training data, research on generalization, creating RL environments to improve Claude models and safety-related tasks, and research and implementation of RL algorithms. - Candidate criteria are similar to ML Systems Fellows. Logistics: - Participants must have work authorization and be located in the US, UK, or Canada during the program. - Shared workspaces are available in San Francisco; remote participation is allowed in the UK, US, or Canada. - Visa sponsorship is not provided; candidates must have or obtain full-time work authorization independently. - The program duration is 4 months full-time, with possible extensions and flexibility for partial commitments. Additional notes: - No guarantee of full-time offers post-program, though strong performers may receive offers or continue impactful AI safety work elsewhere. - Anthropic's full-time role policies do not apply to the Fellows Program. - The company emphasizes collaborative, large-scale AI research with a focus on safety, interpretability, and steerability. - Candidates must be fluent in Python and able to commit full-time. - The program values diversity and encourages applications from underrepresented groups. - Safety advice is provided regarding recruitment communications. Apply at the provided link.

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Anthropic Fellows Program is designed to foster AI research and engineering talent by providing funding and mentorship to promising technical talent regardless of previous experience. Fellows primarily use external infrastructure such as open-source models and public APIs to work on empirical projects aligned with Anthropic's research priorities, aiming to produce public outputs like paper submissions. The program runs for 4 months full-time, with a weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD plus benefits and funding for compute (~$15k/month) and other research expenses. Fellows receive direct mentorship from Anthropic researchers, access to shared workspaces in Berkeley, California or London, UK, and connection to the broader AI safety and security research community. Interview process includes initial application and reference check, technical assessments and interviews, and a research discussion. Candidates are encouraged to apply even if they do not meet every qualification. The program values diversity and representation. Fellows workstreams include AI Safety Fellows, AI Security Fellows, ML Systems & Performance Fellows, Reinforcement Learning Fellows, and The Anthropic Institute Fellows (Economics & Policy). Candidates may be considered for all workstreams by default and can specify preferences. General candidate criteria: motivated by AI safety and societal benefit, strong technical background in computer science, mathematics, or physics, ability to implement ideas quickly and communicate clearly, fluent in Python, and available full-time for the program. AI Safety Fellows focus on research areas such as scalable oversight, adversarial robustness and AI control, model organisms, mechanistic interpretability, and AI welfare. Mentors include Sam Bowman, Sara Price, Alex Tamkin, and others. Candidates with experience in empirical ML research, large language models, and open-source contributions are a good fit. AI Security Fellows focus on reducing catastrophic risks from advanced AI systems, with mentors like Nicholas Carlini and Keri Warr. Candidates with experience in pentesting, vulnerability research, offensive security, CVE reporting, bug bounties, and empirical ML research are preferred. Logistics: applicants must have work authorization and be located in the US, UK, or Canada during the program. Shared workspaces are available in London and Berkeley, with remote options in these countries. Visa sponsorship is not provided. The program duration is 4 months full-time, with possible extensions. Strong performance may lead to full-time offers at Anthropic, though not guaranteed. Applications are currently closed and will be updated when reopened. The program is managed by Constellation recruiting partner. The description includes policies for full-time roles which do not apply to the Fellows Program. Anthropic is a public benefit corporation headquartered in San Francisco offering competitive compensation, benefits, equity donation matching, vacation and parental leave, flexible hours, and office space. The company emphasizes collaborative, high-impact AI research with a focus on steerable, trustworthy AI.

Anthropic is an AI safety and research company building reliable, interpretable AI systems like the Claude family of large language models. About the role Prompts specify what Claude does. Evals measure whether it did. The Product Prompt and Eval Design team handles both for product design: the system prompt greeting new users, tool descriptions deciding whether Claude searches, instructions maintaining quality, and evals testing all of it. The role focuses on building evals that check prompts, the harness running them, and tools enabling designers to do this work independently. It involves close collaboration with surface owners, engineers, and prompt engineering teams during model releases. Key responsibilities: — Write and revise prompts behind Claude's tools, features, and behaviors on product surfaces; test, fix, ship, and confirm prompts. — Build graders to validate prompt fixes and rerun on new models; automate evals from designers' rubrics and analyze transcripts. — Develop visual, low-code eval tools for designers without engineering help: assemble comparison sets, convert rubrics into graders, compare prompt variants, and present results. — Observe designers using tools and simplify them. — Support model releases by testing surfaces, writing prompt fixes and migrations, and creating prompts for new features. — Establish and scale the eval harness to test 50-100 tools with reliable settings, maintain eval stability across models, and diagnose regressions. — Package issues unfixable by prompting for training, including graders, human-feedback questions, and good/bad pairs. Minimum qualifications: — Production-quality Python. — Experience building and maintaining evaluation pipelines for LLM products: graders, rubrics, comparison sets, regression suites, and their orchestration. — Experience creating internal tools with user-friendly interfaces for non-coders. — Experience setting up test harnesses, sandboxing tool calls, and stabilizing settings for comparable runs. — Experience shipping prompts or working closely with prompt shippers, understanding prompt failures across models. — Ability to read transcripts beyond scores. Preferred qualifications: — Experience within a model-launch cycle. — A/B testing experience linking offline evals to online outcomes. — Front-end or notebook-to-app experience and insights on eval result legibility. — Experience converting product rubrics into training signals: graders, human-feedback questions, or preference pairs. — Concern for Claude's behavior for users, beyond metric changes. Logistics: — Minimum education: Bachelor’s degree or equivalent. — Location-based hybrid policy: at least 25% office presence expected. — Visa sponsorship available with legal support. Anthropic values diversity and encourages applications from underrepresented groups. The company emphasizes AI safety and ethical implications, fostering a collaborative environment focused on impactful AI research. Compensation: — Annual salary range: $305,000 - $385,000 USD. Work location: — Hybrid in San Francisco or New York offices.