Research Engineer, Code RL (Reinforcement Learning)

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.

Responsibilities

• Design RL environments and coding tasks
• Build reward signals and verifiers capturing 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
• Improve the speed and reliability of the pipelines that make all of that iterate fast

Requirements

• Strong software-engineering skills and deep Python expertise, including async/concurrent programming
• Comfortable owning systems end to end and debugging across the stack
• Career in research exploration and engineering implementation, engaging rigorously in shaping experimental design and interpreting results
• Care about code quality, testing, and performance
• Passionate about the potential impact of AI and committed to developing safe and beneficial systems

Qualifications

• Bachelor’s degree or an equivalent combination of education, training, and/or experience
• A field relevant to the role as demonstrated through coursework, training, or professional experience

Skills

• 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

Benefits

• Annual compensation range: $500,000—$850,000 USD
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or 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.

Pay

• Annual Salary: $500,000—$850,000 USD

Schedule

• 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.