Research Engineer
Mind Robotics, Palo Alto
What you will do
- Design and implement scalable systems for training large ML models.
- Enable efficient workflows for data ingestion, training, and iteration.
- Develop and optimize distributed training systems across hundreds of GPUs.
- Implement strategies for parallelization, sharding, and efficient compute utilization.
- Improve training efficiency through techniques such as attention optimizations, kernel fusion, and memory management.
- Partner closely with modeling teams to accelerate iteration speed and reduce training costs.
- Build internal tools for experiment tracking, monitoring, and debugging.
- Implement systems for tracking training performance, failures, and resource utilization.