# Anthropic Research Resident at Anthropic

> Carry out a scoped empirical AI research project with mentorship from Anthropic researchers, working toward full-time AI safety work.

- Company: Anthropic (anthropic.com)
- Location: San Francisco, CA | New York City, NY
- Places: San Francisco, New York, United States
- Posted: 2026-10-28
- Team: Anthropic Residency research program
- Work mode: On site
- Type: Temporary
- Pay: Paid, fixed-term program
- Apply: https://job-boards.greenhouse.io/anthropic/jobs/5438311008
- Page: https://ye.saranatour.dev/jobs/anthropic-research-resident-anthropic-kn70btf703350as80z47tt5ve98hcw9z

## The posting

Anthropic Research Resident
Anthropic · San Francisco, CA | New York City, NY

## **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.

## **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

## **Interview process**

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](https://www.linkedin.com/in/sara-price-310757b2/): leads the Alignment Training team; background in data science
- [Ethan Perez](https://ethanperez.net/): leads the Alignment Science team; background in machine learning
- [Evan Hubinger](https://evhub.github.io/): leads the Alignment Stress-Testing team; formerly at The Machine Intelligence Research Institute (MIRI)
- [Samuel Marks](https://scholar.google.com/citations?user=fW7yK10AAAAJ&hl=en): leads the Scalable Oversight team; background in mathematics
- [Elana Simon](https://elanapearl.github.io/): researches the interpretability of language models and biological models; background in biomedical informatics
- [Belinda Li](https://belindal.github.io/): researches how language models represent the world, users, and themselves; background in natural language processing (PhD, MIT)
- [Jack Lindsey](https://jlindsey15.github.io/): leads the Model Psychology team; background in theoretical neuroscience
- [Nicholas Carlini](https://nicholas.carlini.com/): researches adversarial machine learning and AI security; previously at DeepMind and Google Brain
- [Jascha Sohl-Dickstein](https://sohldickstein.com/): works at the intersection of safety and