Research Engineer, Code RL (Reinforcement Learning)

— teaching Claude to write correct, fast code for accelerators

Research Engineer, Universes

— long-horizon, ultra-realistic agentic training environments

— RL for security-relevant coding capabilities

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.

Annual Salary:

$500,000

—

$850,000 USD

Logistics

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.

You'll design RL environments and coding tasks, build the reward signals and verifiers that capture what "good code" means, run training experiments on frontier models, diagnose why a model does (or doesn't) get better at a class of software-engineering work, and improve the speed and reliability of the pipelines that make all of that iterate fast.

Code RL spans several focus areas — from agentic coding behaviors and code correctness, to long-horizon autonomous engineering, to high-performance code for accelerators — and we'll match you to the area where you'll have the most impact.

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