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. 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.
You may be a good fit if you:

• Have strong software-engineering skills and deep Python expertise, including async/concurrent programming
• Are comfortable owning systems end to end and debugging across the stack
• Can balance research exploration with engineering implementation, and engage rigorously in shaping experimental design and interpreting results
• Care about code quality, testing, and performance
• Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems

Strong candidates may also have:

• Experience with reinforcement learning, RLHF, post-training, or LLM finetuning
• Built coding agents, code-execution sandboxes, eval harnesses, verifiers, or developer tooling
• Background in program analysis, testing, verification, compilers, or formal methods
• Experience with PyTorch and large-scale distributed training; performance profiling and optimization of ML systems
• CUDA / GPU or TPU kernel experience and accelerator-performance intuition
• Experience with virtualization and sandboxed code execution environments

Related roles

If your background leans toward one of these areas specifically, you may also want to look at these postings:

• Research Engineer, Performance RL (Reinforcement Learning) - teaching Claude to write correct, fast code for accelerators
• Research Engineer, Universes - long-horizon, ultra-realistic agentic training environments
• Research Engineer, Cybersecurity RL (Reinforcement Learning) - RL for security-relevant coding capabilities

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.

Annual Salary:

$500,000-$850,000 USD

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.