Anthropic Fellows Program

Details

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The Anthropic Fellows Program is designed to foster AI research and engineering talent. Fellows are provided funding and mentorship to promising technical talent—regardless of previous experience.

What to Expect

• 4 months of full-time research
• Direct mentorship from Anthropic researchers
• Access to a shared workspace (in either Berkeley, California or London, UK)
• Connection to the broader AI safety and security research community
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (benefits vary by country)
• Funding for compute (~$15k/month) and other research expenses

Compensation

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

Fellows Workstreams

The program expands across teams at Anthropic, and candidates may be considered for multiple workstreams.

Workstreams include:

1. AI Safety Fellows
2. AI Security Fellows
3. ML Systems & Performance Fellows
4. Reinforcement Learning Fellows
5. The Anthropic Institute Fellows (Economics & Policy)

Across the Workstreams, you may be a good fit if you

• Are motivated by making sure AI is safe and beneficial for society as a whole
• Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic
• Have a strong technical background in computer science, mathematics, or physics
• Thrive in fast-paced, collaborative environments
• Can implement ideas quickly and communicate clearly

Strong candidates may also have

• Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)
• Experience in areas of research or engineering related to their workstream

Candidates must be

• Fluent in Python programming
• Available to work full-time on the Fellows program

AI Safety Fellows

Mentors, research areas, & past projects

Potential mentors include: Sam Bowman, Sara Price, Alex Tamkin, Nina Panickssery, Trenton Bricken, Logan Graham, Jascha Sohl-Dickstein, Joe Benton, Fabien Roger, Samuel Marks, Kyle Fish, Ethan Perez.

Fellows will be matched to projects aligned with research priorities, including:

• Scalable Oversight
• Adversarial Robustness and AI Control
• Model Organisms
• Model Internals / Mechanistic Interpretability
• AI Welfare

Unique candidate criteria

You might be a particularly great fit if you:

• Are motivated by reducing catastrophic risks from advanced AI systems
• Have experience with empirical ML research projects
• Have experience working with large language models
• Have experience in one of the research areas mentioned above
• Have a track record of open-source contributions

AI Security Fellows

Mentors, research areas, & past projects

Potential mentors include: Nicholas Carlini, Keri Warr, Evyatar Ben Asher, Keane Lucas, Newton Cheng.

Unique candidate criteria

You might be a particularly great fit if you:

• Are motivated by reducing catastrophic risks from advanced AI systems
• Have contributed to open-source projects in LLM- or security-adjacent repositories
• Have demonstrated success in bringing clarity and ownership to ambiguous technical problems
• Have experience with pentesting, vulnerability research, or other offensive security work
• Have a demonstrated willingness to do the "dirty work" that produces high-quality outputs
• Have reported CVEs or been awarded bug bounties
• Have experience with empirical ML research projects
• Have experience with deep learning frameworks and experiment management

ML Systems & Performance Fellows

Mentors, research areas, & past projects

Potential mentors include: Alwin Peng, Zygi Straznickas.

Projects may include:

• Building a CPU simulator for accelerator workloads
• Adding backends for different accelerators on an open source project
• Building on demand infrastructure for other infrastructure heavy fellows projects
• Building complex synthetic data or environment pipelines

Unique candidate criteria

You might be a particularly great fit if you:

• Have strong software engineering skills with experience building complex ML systems
• Can balance research exploration with engineering rigor and operational reliability
• Enjoy collaborating across research and engineering disciplines
• Are comfortable working with large-scale distributed systems and high-performance computing (e.g. in trading)
• Have experience with training, fine-tuning, or evaluating large language models
• Are adept at analyzing and debugging model training processes

Reinforcement Learning Fellows

Mentors, research areas, & past projects

Potential mentors include: Ruhua Jiang, Kaidi Cao, Sunny Duan, David Brandfonbrener, Colt Steele, Dino Distefano, Will Williams.

Projects may include:

• Building model-based tools to better understand AI training data and improve training data quality
• A research project to better understand generalization
• Creating RL environments to improve Claude models at capabilities within your domain of expertise
• Building RL environments for safety-related tasks
• Conducting research and implementing solutions in areas such as RL algorithms

Unique candidate criteria

You might be a particularly great fit if you:

• Have strong software engineering skills with experience building complex ML systems
• Can balance research exploration with engineering rigor and operational reliability
• Enjoy collaborating across research and engineering disciplines
• Are comfortable working with large-scale distributed systems and high-performance computing
• Have experience with training, fine-tuning, or evaluating large language models
• Are adept at analyzing and debugging model training processes

The Anthropic Institute Fellows (Economics & Policy)

Mentors, research areas, & past projects

Potential research areas and mentors include:

• Economics (Maxim Massenkoff, Peter McCrory)
• Policy, Security, and Society (Jack Clark, Marina Favaro, Jim Baker)

Projects may include:

• Designing and conducting empirical research on AI's economic effects, drawing on external data sources
• Developing new methodological approaches for studying AI's impact on labor markets, the future of work, and society
• Analysing the offense–defense balance for AI-enabled cyber and bio capabilities as models scale
• Measuring the extent to which model performance increases with custom harnesses?
• Identifying market driven mechanisms that could improve societal resilience to anticipated threats from AI systems?
• Identifying which metrics relating to AI R&D could service as early warning signals for recursive self-improvement

Unique candidate criteria

You might be a particularly great fit if you:

• Have an interest in economics or policy research; prior experience is a plus but not required
• Are adaptable and collaborative, able to take direction and contribute to team priorities
• Are skilled at writing up and communicating your results, even when they're null or unexpected
• Are passionate about translating research insights into actionable recommendations for improving AI systems and informing policy

Logistics

Logistics Requirements

To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program.

Workspace Locations

Shared workspaces are designated in London and Berkeley where fellows will work from and mentors will visit. Remote fellows are also open in the UK, US, or Canada. Fellows will be asked about availability to work from Berkeley or London (full- or part-time) during the program.

Visa Sponsorship

We are not currently able to sponsor visas for fellows. You need to have or independently obtain full-time work authorization in the UK, the US, or Canada.

Program Duration

• Program runs for 4 months, full-time.
• If you can’t commit to the full duration, you can still apply and note your constraints; requests are reviewed case-by-case.

Interview process

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

Notes on applying

Applications close for the next cohort at 11:59pm PT on July 26. The cohort is expected to start November 2 (some circumstances may allow different start dates). Applications are managed by Constellation.