ML Infra Engineer, Platform
Physical Intelligence10 hours ago
Responsibilities
- Operate and evolve Kubernetes clusters and scalable service deployment patterns.
- Build internal platform systems such as evaluation services, operational tooling, and APIs with safe rollout, upgrade, and rollback strategies.
- Develop security, logging, metrics, tracing, alerting, reliability, and cost-visibility infrastructure.
- Design authentication and authorization flows, networking architecture, quota and rate-limiting services, and multi-cloud infrastructure primitives.
- Standardize infrastructure patterns, abstractions, and interfaces to reduce operational churn.
- Improve local and remote development workflows and self-service infrastructure usage.
- Own infrastructure systems end-to-end from design through operation and collaborate with researchers and engineers on ambiguous requirements.
Requirements
- 4-6 years of experience working in fast-moving or early-stage environments with demonstrated growth.
- Deep experience with GCP, AWS, distributed systems, compute orchestration, networking, autoscaling, service meshes, and load balancing.
- Comfort with Kubernetes, cluster-level reliability, and service-oriented architectures.
- Experience with infrastructure-as-code such as Terraform, containerization, and modern platform engineering practices.
- Familiarity with agent infrastructure, observability, security, sandboxing, logging, metrics, tracing, incident response, SLOs, and distributed-systems debugging.
- Ability to reason about scalability, bottlenecks, performance tuning, failure modes, and cost optimization across compute, networking, and storage.
- Strong first-principles thinking, cross-functional communication, and end-to-end ownership.
- Bonus experience with large-scale ML training, evaluation or simulation infrastructure; secrets management such as Doppler; observability; cost optimization; internal platform tooling; robotics; simulation; or real-time systems.
Categories
About Physical Intelligence
Physical Intelligence builds general-purpose AI for the physical world, developing foundation models and full-stack robotic systems for robots and other actuated devices. The privately held company was founded in 2024 and focuses on taking designs from prototype to high-volume production, including actuation, mechatronics, and manufacturing process development. Its work aims to power today’s robots and future hardware across industries.