Research, RL Scaling

Company

Thinking Machines Lab

Where

San Francisco

Level

Mid

First seen

October 21, 2026

Postings

2

Listed via

Ashby

What the posting says

A center of gravity for this role is asynchronous RL. Decoupling generation from training changes both the systems design and the learning problem, and doing it well requires a deep understanding of async RL algorithms, design choices, and trade-offs on both the ML and the systems sides. We expect much of the headroom in RL scaling to come from here. Because generation dominates the cost of RL at scale, good knowledge of inference systems, low-precision numerics, and quantization is recommended: you should be able to reason quantitatively about rollout throughput and cost (batching, KV…

Read more and apply on Thinking Machines Lab's site

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