ML Infra Engineer, Data Systems
Physical Intelligence · San Francisco
CHECKED 15H AGO
Roboticsonsite
At a glance
Highlights
- Build data infrastructure powering large-scale robot learning end to end.
- Design high-throughput pipelines that validate and featurize raw multimodal data.
- Move petabytes efficiently across clusters while ensuring correctness at scale.
Ideal candidate
Systems-minded engineer who loves owning petabyte-scale data systems end to end and cares about performance and reliability. You thrive collaborating with researchers to unblock fast-moving robot learning.
Requirements
- Strong software engineering fundamentals.
- Experience building distributed systems or large-scale data pipelines.
- Comfort reasoning about performance, memory, I/O, and storage efficiency.
- Familiarity with batch and/or streaming processing systems.
- Experience with object storage systems and data format tradeoffs.
- Ownership mindset: design, build, operate, and iterate on systems end-to-end.
- Enjoy working closely with researchers and unblocking fast-moving projects.
Lab profile
About Physical Intelligence
Developing general-purpose AI foundation models to power robots for any physical task.
What they build
- General-purpose robot foundation models
- Learning algorithms for robot control
- Robotic systems and platforms
Known for
- Foundation model and system-building research
- Large-scale multimodal robot data operations
- Real-world fleet deployment and operations
- Prototype-to-production hardware engineering