- Cambridge, Massachusetts, United States +1 more
- Full-time
- $148K–$240K per year
- 4+ years
Lead performance optimization for large language model training and inference on NVIDIA GPU clusters, improving GPU utilization, memory footprint, and distributed training efficiency.
Locations (2)
- Cambridge, Massachusetts, United States
- San Francisco, California, United States
Compensation
Expected Base Salary Range $148,000—$240,000 USD
Responsibilities
- Profile and optimize GPU compute kernels for large language models
- Optimize GPU cluster performance for collective/MoE frameworks and RDMA/IB/EFA usage
- Manage big data pipelines for mid-training scale data
- Optimize reinforcement learning pipelines and async cycles
- Ensure optimized configurations are tested, accessible, and adaptable for research tasks
Requirements
- Bachelor's or Master's in Computer Science or related quantitative field
- PhD in a relevant research area