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.
Apply using this link. We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you.
This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.
Anthropic Fellows Program overview
The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.
Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.
We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.
What to expect
Interview process
The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
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 (these vary by country)
Funding for compute (~$15k/month) and other research expenses
Compensation
The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).
Fellows workstreams
Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams.
Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below:
This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.
AI Safety Fellows
AI Security Fellows
ML Systems & Performance Fellows
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
Reinforcement Learning Fellows
Mentors, research areas, & past projects
Fellows will undergo a project selection & mentor matching process. Potential research areas and mentors include:
Fluent in Python programming
Available to work full-time on the Fellows program
Ruhua Jiang
Kaidi Cao
Sunny Duan
Projects in this workstream may include
Unique candidate criteria
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 that are within your domain of expertise
Building RL environments for safety-related tasks
Conducting research and implementing solutions in areas such as RL algorithms
You might be a particularly great fit for this workstream if you
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: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your 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. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada.
Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis.
Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations.
Applications and interviews are managed by Constellation, our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds.
Apply here
The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program. Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
This role is synchronized from the company's public greenhouse feed. The company application page is the source of truth.
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. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
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
