Research Scientist, AI Networking (PhD)
Tasks
- Build software benchmarks and performance tuners
- Develop NCCL based distributed training stack
- Enable scalable distributed ML training
- Improve distributed GPU communication reliability and performance
- Integrate and optimize communication for PyTorch
- Perform HPC and parallel computing optimizations
- Work on GenAI and LLM scaling reliability and performance
Perks/Benefits
- N/A
Skills/Tech-stack
CUDA | Data-parallel | Deep learning | Distributed Data Parallel | Distributed data | Distributed machine learning | Fully Sharded Data Parallel | GPU Architecture | High Performance | High-Performance Computing | Infiniband | Language Models | Large Language Models | Machine Learning | NCCL | Parallel Computing | Performance Computing | Pipeline Parallel | PyTorch | RoCE | Tensor Parallel | TensorFlow
Education
Roles
Engineer | Research Scientist | Scientist | Software Engineer
Regions
Countries
States
Cities
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