Nous Research
4 open roles on Maneki
Full TimeMLE (Reinforcement Learning Training Infrastructure)
Mid / Senioron site
LOCATION
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POSTED
8mo ago
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Required skills
Machine LearningReinforcement LearningDistributed ComputingMicroservicesPerformance Engineering
Job description
We’re looking for an MLE to build and scale distributed reinforcement learning systems for model training. You’ll deploy elastic environment microservices, design reward systems and optimize multi-node and multi-datacenter training pipelines.
Responsibilities:
- Designing and implementing RL pipelines from reward modeling to policy optimization
- Optimizing RL training stability and sample efficiency for large models
- Verifying numerical correctness across inference and training
- Performance engineering on trainer-inference communication
- Validating methods from recent publications
Qualifications:
- Hands-on experience with reinforcement learning in production systems
- Deep understanding of policy-space methods (GRPO, PPO, etc.)
- Experience profiling distributed systems
Preferred:
- History of OSS contributions
- Knowledge of TorchTitan and SGLang or vLLM