Primary record

Research Engineer, Code RL (Reinforcement Learning)

Anthropic Indexed employerSan Francisco, CA | New York City, NY · San Francisco, California, United States
Source-hosted applyChecked 4h agoInternship
Apply at Anthropic

Anthropic receives this application through Greenhouse. Babu Careers does not claim delivery.

Workplace

hybrid

Employment

Internship

Published

Aug 11, 2026

Closes

No date supplied

The 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.

About the RL Teams

Our Reinforcement Learning teams play a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of our latest Claude models. Our work spans several key areas:

Developing systems that enable models to use computers effectively

Advancing code generation through reinforcement learning

Pioneering fundamental RL research for large language models

Building scalable RL infrastructure and training methodologies

Enhancing model reasoning capabilities

We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish.

About the Role

We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to write, edit, test, debug, and ship real software — end to end, on real codebases, with real tools — and to do it correctly, fast, and safely.

This role blends research and engineering

Requirements

Department: AI Research & Engineering