Research Engineer, Robot Foundation Models
Mind Robotics, Palo Alto
What you will do
- Scale and harden large-scale distributed training, from parallelism strategy to checkpointing and fault tolerance.
- Profile and speed up the training stack end to end, and track throughput and cost per run.
- Build high-throughput data loading for multimodal robot data, from raw logs to the GPU.
- Make experiments easy to launch, monitor, debug and reproduce, and run your own ablations alongside the researchers.
- Make evaluation fast, and get models running on the robot within its latency budget.
- Build whatever the work needs, and own the problem end to end.