Senior Distributed ML Engineer
Posted Updated
Description
You will work with researchers to accelerate distributed model training and inference. You will investigate performance bottlenecks, optimize computing resources, develop orchestration tools and libraries, and establish documented best practices for large-scale machine-learning workflows.
Responsibilities
- Collaborate with researchers on large-scale model training and inference
- Investigate performance bottlenecks and debug research experiment code
- Optimize computing-resource utilization
- Develop tools and libraries for distributed research experiments
- Establish, document, and maintain distributed ML development practices
Requirements
- Degree in a relevant computer science field
- 3 or more years designing and implementing distributed ML training frameworks
- Experience with Megatron, DeepSpeed, HuggingFace Accelerate, FSDP, vLLM, or verl
- Experience with cloud platforms such as AWS, GCP, or Azure
- Experience with Ray or Slurm
- Experience with PyTorch Profiler, PyProf, or NVIDIA Nsight
- Familiarity with gRPC, Docker, or Kubernetes
- Familiarity with vector databases
- Track record contributing to deep-learning research projects
Benefits
- Comprehensive health benefits including mental health and wellness management account
- 20 vacation days per year from the start date
- 4% employer retirement savings contribution with no employee match