Anthropic Fellows Program, AI Safety & Security
Anthropic is hiring an Anthropic Fellows Program, AI Safety & Security in London and San Francisco. Level rates it ; you can apply on Anthropic.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- Some of the work can be done remotely, according to the posting.
- The posting mentions AI agents, AI safety and AI research among its tools and skills.
- Anthropic has 680 other open roles on Level.
AI in this role
About Anthropic
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.
Applications are now open for our January cohort - apply here by October 30.
Anthropic Fellows Program overviewThe 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.
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 (these vary by country)
- Funding for compute (~$15k/month) and other research expenses
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.
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).
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
Mentors, research areas, & past projects
Fellows will undergo a project selection & mentor matching process. Potential mentors include:
- Sam Bowman
- Sara Price
- Alex Tamkin
- Nina Panickssery
- Trenton Bricken
- Logan Graham
- Jascha Sohl-Dickstein
- Joe Benton
- Collin Burns
- Fabien Roger
- Samuel Marks
- Kyle Fish
- Ethan Perez
Our mentors will lead projects in select AI safety research areas, such as:
- Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains.
- Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.
- Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise.
- Model Internals / Mechanistic Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures.
- AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations.
On our Alignment Science and Frontier Red Team blogs, you can read about past projects, including:
- Subliminal Learning: Language Models Transmit Behavioral Traits via Hidden Signals in Data: Alex Cloud and Minh Le, et al., mentors including Samuel Marks and Owain Evans
- Open-source circuits: Michael Hanna and Mateusz Piotrowski with mentorship from Emmanuel Ameisen and Jack Lindsey
For a full list of representative projects for each area, please see these blog posts: Introducing the Anthropic Fellows Program for AI Safety Research, Recommendations for Technical AI Safety Research Directions.
Unique candidate criteria
You might be a particularly great fit for this workstream 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
Mentors, research areas, & past projects
Fellows will undergo a project selection & mentor matching process. Potential mentors include:
- Nicholas Carlini
- Keri Warr
- Evyatar Ben Asher
- Keane Lucas
- Newton Cheng
On our Alignment Science and Frontier Red Team blogs, you can read about some past Fellows projects, including:
- AI agents find $4.6M in blockchain smart contract exploits: Winnie Xiao and Cole Killian, mentored by Nicholas Carlini and Alwin Peng
- Strengthening Red Teams: A Modular Scaffold for Control Evaluations: Chloe Loughridge et al., mentored by Jon Kutasov and Joe Benton
Unique candidate criteria
You might be a particularly great fit for this workstream 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
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 and program partner. 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 by October 30.
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
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.
How we rate this
Anthropic Fellows Program, AI Safety & Security at Anthropic rates 88 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a research question you investigated. What did you find?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI agents, AI Safety, and AI Research. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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