Machine Learning Engineer — Reinforcement Learning

Sunnyvale, CAfull timeOn Site$150k–$450kH1B: no

Ifm US Machine Learning Engineer — Reinforcement Learning develops and scales end-to-end RL training systems. The role works closely with researchers and engineers to extend distributed training frameworks and improve training system reliability and performance.

Responsibilities

We’re looking for an RL infrastructure engineer to help extend and scale our end-to-end RL training systems. You’ll work side-by-side with world-class researchers and engineers to:
Extend distributed training frameworks (e.g., DeepSpeed, FSDP, FairScale, Horovod)
Integrate rollout generation, reward computation, trajectory processing, policy updates, and weight synchronization
Build robust config + launch systems across multi-node, multi-GPU clusters
Own experiment tracking, metrics logging, and job monitoring for external visibility
Improve training system reliability, maintainability, and performance
Hands-on experience developing end-to-end RL infrastructure is required. Strong infrastructure and systems experience is what we value most.