Senior Software Engineer, RL Post-Training Frameworks
US, CA, Santa Clara, United States
USD 184K-356K Senior-level Full Time
Tasks
- Architect RL post training infrastructure
- Build distributed RL training inference rollout loops
- Coordinate actor critic and reward models across heterogeneous hardware
- Design distributed systems failure recovery and recovery approaches
- Implement fault tolerance elastic scaling and fast restarts
- Improve open source RL frameworks
- Integrate CPU driven rollout workloads for tool use code execution and agent environments
- Partner with framework owners and research teams
- Tune performance for GPUs CPUs and LPUs
Perks/Benefits
Skills/Tech-stack
Actor Based Programming | C# | C++ | Consistency models | DPO | DeepSpeed | Distributed Systems | FSDP | FSDP2 | Failure recovery | GRPO | High Performance | High-Performance Computing | High-performance inference | Infiniband | Kubernetes | LLM post training | MOE | Megatron-LM | Mixed Precision | NCCL | NVLink | PPO | Performance Computing | Pipeline parallelism | Post-training | PyTorch | Python | Quantization aware training | RLHF | Ray | Reinforcement Learning | Reinforcement Learning for LLM Post Training | Reward Modeling | Service boundaries | Task-based programming | Tensor Parallelism | TensorRT-LLM | VLLM
Education
Regions
Countries
States
Cities
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