ML Infra Engineer, Platform

Job summary

Responsibilities

The Infrastructure team builds and operates the backbone of everything PI does: from training state-of-the-art VLA models, to orchestrating large-scale simulation, to reliably deploying intelligence across fleets of physical robots.

• Own and scale AI-native infrastructure: You will operate and evolve Kubernetes clusters and service deployment patterns, and help build a scalable microservice platform for…
• Drive security, observability and cost-aware infrastructure: You will treat security, logging, metrics, tracing, and alerting as first-class platform primitives, and build…
• Harden platform foundations: You will own core infrastructure with multi-cloud considerations, designing authentication/authorization flows, networking architecture, quota and…
• Improve developer experience: You will build clear, documented interfaces for using platform infrastructure, reducing the gap between “I need infra” and “I can run my workload.”…
• Collaborate and lead through ownership: You will work closely with researchers and other engineers to understand requirements and constraints, translate fast-moving needs into…

What they're looking for

• Extremely strong first-principles thinking.
• Familiarity with agent infrastructure, observability, security and sandboxing
• Deep experience with cloud platforms (GCP, AWS) and distributed systems: compute orchestration, networking, autoscaling, service meshes, load balancing.
• Ability to reason about system bottlenecks, performance tuning, and cost optimizations across compute, networking, and storage.
• Comfort with Kubernetes, cluster-level reliability, and service-oriented architectures.

Tech stack

• Kubernetes
• GCP
• AWS
• Terraform