Research Engineer, Training & Inference
Tasks
- Architect RL agent systems for high throughput
- Build RL training and serving infrastructure
- Identify and resolve performance bottlenecks in distributed clusters
- Maximize RL throughput from data generation to training
- Optimize high performance inference for low latency
- Optimize memory efficiency for large models
- Tune inference engine router and scheduler
Perks/Benefits
Skills/Tech-stack
C++ | CUDA | Cutlass | Distributed Training | FSDP | Inference Optimization | JAX | NCCL | PyTorch | Python | Reinforcement Learning | Tensor Parallelism | TensorFlow | Triton
Education
Regions
Countries
States
Cities
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