Anthropic Research Resident

anthropic; Greater London; Remote; GBP 265,000 - 375,000; Full time

Benefits offered by this job

Visa sponsorship

Remote work options

Job summary

Anthropic is offering a paid residency program aimed at researchers, engineers and leaders transitioning to full-time safety-focused AI work. The six-week to six-month placement provides direct mentorship, access to Claude models and GPU compute, and engagement with a broader AI safety community.

Ideal candidates are proven in technical fields and eager to contribute to empirically driven AI research, with or without a traditional machine learning background.

Qualifications

• Bachelor’s degree required or equivalent experience.
• Experience leading ambitious work in technical fields is valued.
• Background in machine learning not strictly required.

Responsibilities

• Engage in empirical AI research projects with mentorship from Anthropic researchers.
• Contribute to AI safety and alignment research initiatives.
• Collaborate across research, engineering and policy disciplines.

Skills

Lead ambitious work in technical areas

Empirical AI research

Able to transition to full-time roles

Strong communication

Education

Bachelor’s degree

Tools

Kubernetes

Job description

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

The Anthropic Residency is our paid, fixed-term research program, with placements lasting between six weeks and six months. We are looking for people who have led ambitious work in a variety of technical fields and want to transition to full-time work focused on making sure AI systems are safe and beneficial for all of humanity. If you are a professor in a quantitative discipline, a technical founder or a staff-level engineer and want to transition to work on transformative AI, we want to hear from you. Background in machine learning is not required.

What to expect

• A concrete, scoped project matched to your background, with direct mentorship from Anthropic researchers
• Access to Claude models and GPU compute
• Connection to the broader AI safety and security research community

The interview process will include an initial application, recruiter screen, technical assessment, research discussion and a reference check.

Applications for this round close on November 22, 2026 (11:59 PM PT). We expect to make offers in January 2027.

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 working on empirical AI research full-time
• Have led ambitious work in a variety of technical fields (professor in a quantitative discipline, a technical founder or a staff-level engineer)
• Thrive in fast-paced, collaborative environments
• Can implement ideas quickly and communicate clearly

Strong candidates may also

• Have experience authoring research papers in machine learning, NLP, or AI safety
• Have experience with LLMs, reinforcement learning or Kubernetes clusters and complex shared codebases

Mentors and research areas

Potential Anthropic mentors include:

• Sara Price : leads the Alignment Training team; background in data science
• Ethan Perez : leads the Alignment Science team; background in machine learning
• Evan Hubinger : leads the Alignment Stress-Testing team; formerly at The Machine Intelligence Research Institute (MIRI)
• Samuel Marks : leads the Scalable Oversight team; background in mathematics
• Elana Simon : researches the interpretability of language models and biological models; background in biomedical informatics
• Belinda Li : researches how language models represent the world, users, and themselves; background in natural language processing (PhD, MIT)
• Jack Lindsey : leads the Model Psychology team; background in theoretical neuroscience
• Nicholas Carlini : researches adversarial machine learning and AI security; previously at DeepMind and Google Brain
• Jascha Sohl-Dickstein : works at the intersection of safety and pretraining; background in physics and neuroscience, formerly Principal Scientist at Google Brain

Residents will work on empirical research questions in collaboration with Anthropic's research teams. Areas we are particularly interested in include:

AI safety & alignment

• 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 Internals and Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures.
• Safeguards Research: Developing robust defenses against adversarial attacks, comprehensive evaluation frameworks for model safety, and automated systems to detect and mitigate potential risks before deployment.
• AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations.

AI security & frontier red-teaming

• Stress-testing frontier models to understand the full extent of their current capabilities in fields such as cybersecurity, robotics or cryptography.

ML systems & reinforcement learning

• Improving how frontier models are trained and building the infrastructure behind that research, from model architecture, optimizers and training data to accelerator simulators, hardware backends and RL environment pipelines.
• Duration: Placements are six weeks, three months or six months, depending on team fit and candidate preferences. Other lengths between three and six months are possible by exception.
• Location: This application is for a remote UK position, with the option to work from our London office. However, we prefer that Residents work from our San Francisco office, where most of our research staff is based, but remote participation is possible, especially for shorter placements. Most full-time research roles at Anthropic require relocation to San Francisco. Remote participants need to be based in a country where Anthropic can hire.
• Commitment: Full-time role for the duration of the residency.
• Compensation: £265,000 to £375,000/year pro-rated for the duration of the residency + benefits
• Visa sponsorship: We sponsor visas for placements of three months or longer. For six-week placements we encourage remote participation from a country where Anthropic can hire.

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

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.

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

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