
ML Infrastructure Engineer
Sunday Robotics6 months ago
Foster City, CA, USAMid Level
H1B Sponsor
Responsibilities
- Maintain an effective research codebase optimized for fast iteration and correctness.
- Own model-training infrastructure for job scheduling, checkpointing, metrics, and logging.
- Scale distributed training across GPU clusters and enable larger models through sharding, activation checkpointing, and memory optimization.
- Profile and optimize GPU utilization, memory usage, and training throughput.
- Build low-latency inference pipelines for real-time robot control and optimize inference performance through quantization, distillation, and model compilation.
- Collaborate with researchers and roboticists to translate research needs into reliable software and infrastructure.
- Design high-throughput pipelines for ingesting, validating, and transforming multimodal robot data.
- Build storage systems and metadata indexing for large-scale dataset management.
- Optimize dataloaders, sharding, and prefetching to reduce the time from data arrival to model training.
- Build research tools for debugging, visualization, and experiment analysis.
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.
- Ability to reason about performance, memory, I/O, and GPU utilization.
- Experience managing training workloads with SLURM, Kubernetes, or similar tools.
- Ability to design, build, operate, and iterate on systems end-to-end.
- Willingness to work closely with researchers and unblock fast-moving projects.
- Nice to have experience with robotics data pipelines or multimodal models.
- Nice to have a background in VLAs, Video Generation architectures, or robot-learning systems.
- Nice to have deep ML systems experience with training compilers, custom kernels, or runtime optimization.
- Nice to have hands-on GPU performance-tuning experience.
- Nice to have experience with Protobuf, FlatBuffers, or MCAP.
Tech Stack
Categories
Data EngineeringML Engineering
About Sunday Robotics
The helpful home robot company