Latest AI JobsBrowse Jobs
P

ML Infra Engineer, Platform

physicalintelligenceSan FranciscoMachine Learning
Apply on company site
Salary
Not listed
Job type
Full-time
Experience
Mid · 4+ yrs
Posted
9 Oct 2026
Status
Open · checked 7d ago

About this role

ML Infra Engineer, Platform is a full-time position based in San Francisco with physicalintelligence, designed for professionals seeking to build scalable systems for physical AI applications. This role suits infrastructure specialists with a strong background in distributed systems who want to support foundational robotics models.

Role Overview

physicalintelligence seeks an ML Infra Engineer, Platform in San Francisco to manage and expand the technical backbone supporting foundation models and robotics algorithms. The position centers on creating robust cloud environments that facilitate model training, simulation, and hardware deployment.

Key Responsibilities

Operate and scale Kubernetes clusters, service deployment patterns, and internal microservice platforms.
Integrate security, logging, metrics, tracing, alerting, and cost-visibility mechanisms into the platform.
Design core infrastructure including multi-cloud strategies, networking, authentication flows, and rate-limiting services.
Enhance developer experience by providing documented interfaces, self-serve tools, and consistent development workflows.
Partner with researchers and engineers to translate operational requirements into reusable infrastructure systems.

Requirements

Apply first-principles thinking to resolve technical challenges and address ambiguous domains.
Bring four to six years of professional experience in fast-paced or early-stage settings.
Demonstrate deep expertise in cloud platforms like GCP and AWS alongside distributed systems concepts.
Utilize Kubernetes, infrastructure-as-code tools such as Terraform, containerization, and service-oriented architectures.
Maintain familiarity with observability practices, networking, security, sandboxing, and performance tuning.

Nice to Have

Background in large-scale machine learning training, evaluation, or simulation infrastructure.
Experience utilizing secrets management systems like Doppler.
Exposure to internal platform tooling, cost optimization, robotics, or real-time systems.

Skills and Tools

Kubernetes
Terraform
GCP
AWS
Doppler

About the Company

physicalintelligence develops foundation models and learning algorithms to power robots and physically-actuated devices, bringing general-purpose artificial intelligence into the physical world.

How to Apply

Interested candidates should apply on the official company careers page.

Skills and tech stack

KubernetesTerraformGCPAWSDopplerDistributed Systems

Questions candidates ask

Where is the ML Infra Engineer, Platform position located?

The job is located in San Francisco.

How many years of experience are required?

The role requires four to six years of experience working in fast-moving or early-stage environments.

What core technologies will the engineer use?

The position involves working with Kubernetes, Terraform, cloud platforms like GCP and AWS, and secrets management tools like Doppler.

What does physicalintelligence do?

The company develops foundation models and learning algorithms to power robots and physically-actuated devices.

How should candidates apply?

Candidates should submit their applications directly on the official company careers page.

Ready to apply?

The application is on the official physicalintelligence careers page.

Apply on company site