Research Engineer, Code RL (Reinforcement Learning)

The shape of it

In the posting’s own words

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.

What it asks for · 5

• 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

Also a plus

• 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

Tools and skills named

Words the posting leans on

• code11×
• experience8×
• research engineer7×
• coding6×
• end6×
• performance6×
• reinforcement learning6×
• systems6×
• training5×
• engineering4×
• testing4×
• areas3×
• fast code3×
• models3×
• real3×
• accelerator-performance intuition2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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