ML Infrastructure Engineer
Sunday Robotics5 months ago
Foster City, CA, USAMid Level / Senior
H1B Sponsor
Responsibilities
- Maintain an effective research codebase optimizing for fast iteration and correctness.
- Own infrastructure for model training including job scheduling, checkpointing, metrics, and logging.
- Scale distributed training across GPU clusters with minimal researcher friction.
- Enable training of larger models through sharding and memory optimization.
- Profile and optimize GPU utilization, memory usage, and training throughput.
- Build low-latency inference pipelines for real-time robot control.
- Design high-throughput pipelines for ingesting and transforming multimodal robot data.
- Build storage systems and metadata indexing for efficient dataset management.
Requirements
- Strong software engineering and systems fundamentals.
- Experience building distributed systems or large-scale data pipelines.
- Hands-on experience with ML training infrastructure, ideally PyTorch.
- Comfort with performance, memory, I/O, and GPU utilization.
- Experience managing training workloads using SLURM, Kubernetes, or similar.
- Ownership mindset for designing, building, and operating systems end-to-end.
- Enjoy working closely with researchers to unblock fast-moving projects.
Tech Stack
Categories
AI & MLData Engineering