Research Engineer, Large-Scale Training
Tasks
- Benchmark new approaches
- Build experimental infrastructure
- Design and execute experiments
- Design large-scale training infrastructure
- Enable support for new open source foundation models
- Identify and eliminate performance bottlenecks
- Integrate model architectures
- Optimize training components
- Productionize training methods
- Profile distributed training workloads
- Validate training correctness and convergence
Perks/Benefits
Skills/Tech-stack
CUDA | Communication collectives | Data parallelism | Deep learning | DeepSpeed | Distributed Training | Experimental Design | Expert parallelism | FSDP | GPU Architecture | Machine Learning | Megatron-LM | Mixed Precision | Mixed-precision training | NCCL | Performance Profiling | Pipeline parallelism | PyTorch | Python | Scalability | Tensor Parallelism | Triton
Education
N/A
Roles
Regions
Countries
States
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