ML Infra Engineer, Platform
Physical Intelligence · San Francisco
CHECKED 16H AGO
Roboticsonsitemid-level
At a glance
Highlights
- Operate backbone behind state-of-the-art VLA models and large-scale simulation.
- Scale infrastructure from prototype to production-grade fleets of physical robots.
- Build internal evaluation services and operational tooling for robotics teams.
Ideal candidate
A first-principles owner who thrives in fast-moving, ambiguous environments and cares deeply about bringing general-purpose AI into the physical world by turning research needs into reliable, scalable platforms.
Requirements
- 4-6 years in fast-moving or early-stage environments with demonstrated growth
- Deep experience with cloud platforms (GCP, AWS) and distributed systems
- Comfort with Kubernetes, cluster reliability and service-oriented architectures
- Experience with infrastructure-as-code (e.g. Terraform) and containerization
- Familiarity with logging, metrics, tracing, SLOs and incident response
- Ability to reason about bottlenecks, performance tuning and cost optimization
- Strong cross-functional communication and end-to-end ownership mindset
- Familiarity with agent infrastructure, observability, security and sandboxing
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