---
title: 'Robot Integration Engineer at Physical Intelligence'
canonical: 'https://feeny.ai/job/robot-integration-engineer-physical-intelligence-san-francisco-j846qt1v547v'
type: 'job'
last_seen: '2026-09-06'
---

# Robot Integration Engineer at Physical Intelligence

- **Company:** Physical Intelligence
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-05-18
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/physicalintelligence/8e9830f4-89ba-46e6-ab73-648c550aaf3c/application

**Skills:** Robot systems integration, System verification and validation testing, Mechanical systems, Electrical systems, Software systems, Actuators, PCBs, Cameras, Wiring harnesses, Communication hardware, Integration tooling, Scripting, Automated tests, Data analysis, Technical documentation, Mobile manipulators, Humanoid platforms, Multi-DOF robotic systems, Python, ROS

> The Robot Integration Engineer owns the integration of robot platforms into the fleet, driving closure on system issues across electrical, mechanical, and software interfaces. This role involves defining acceptance criteria, executing fleet acceptance testing, and monitoring platform reliability to ensure successful...

## Job description

## Who We Are

Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.

The Team

The Fleet team owns the readiness, reliability, and operational health of PI’s robot fleet. They partner across hardware, runtime, and forward-deployed engineering to ensure every robot platform is integrated cleanly, performs reliably in the field, and improves over time — directly enabling the data collection and evaluation that powers PI’s foundation models.

In This Role You Will

- Robot Platform Fleet Integration: Be the accountable owner for a robot platform’s successful integration into the fleet, driving closure on system issues across electrical, mechanical, and software interfaces.
- Acceptance Criteria & Metrics: Define acceptance tests, criteria, and passing metrics with clear documentation on test plans.
- Fleet Acceptance Testing: Drive and execute fleet acceptance testing per defined criteria; assess data and results to determine whether robot units can be integrated into the fleet.
- Robot Platform Sustainment: Monitor and maintain the health and performance of the platform in the fleet; create bring-up procedures and troubleshooting guides for Forward Deployed Robotics Engineers.
- Reliability Improvements: Own MTBF for integrated platforms and lead design improvements to push reliability metrics upward.
- Cross-Functional Collaboration: Engage with hardware and software teams to close interface gaps and drive design improvements throughout integration and sustainment.

## What We Hope You’ll Bring

- B.S. in Robotics, Mechatronics, Systems Engineering, Electrical Engineering, or equivalent experience.
- 5+ years of experience with robot systems integration across multiple hardware and software disciplines, including system verification and validation testing.
- Strong understanding of mechanical, electrical, and software interactions in robotic systems, with the ability to resolve complex issues across all three.
- Strong understanding of robotics hardware and electromechanical systems including actuators, PCBs, cameras, wiring harnesses, and communication hardware.
- Software proficiency to build integration tooling, scripts, and automated tests that improve reliability and speed of integration.
- Test execution and data analysis skills — ability to process and analyze data to pull technical insights from results.
- Excellent written and verbal communication, particularly in technical documentation.
- High ownership and ability to thrive in a highly dynamic startup environment.

Bonus Points

- Prior experience integrating mobile manipulators, humanoid platforms, or other complex multi-DOF robotic systems.
- Familiarity with Python, ROS, and tooling for automated test execution and data pipelines.
- Experience operating in a zero-to-one or early-stage fleet/operations environment.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

## About Physical Intelligence

## Company Overview
- **One-liner**: Physical Intelligence is building general-purpose AI foundation models that can control any robot to perform any physical task, aiming to bring the flexibility of large language models into the physical world.
- **Entity Type**: Private (Series A/B stage; total funding $1.07B across multiple rounds)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2024
- **Founders**: Sergey Levine (UC Berkeley), Chelsea Finn (Stanford), Karol Hausman (CEO, ex-Google DeepMind), Lachy Groom (ex-Stripe), Quan Vuong (ex-Google DeepMind), Brian Ichter, and Adnan Esmail

## Core Business
- **Primary industry**: Robotics foundation models / Artificial Intelligence / Research Services
- **Target customers**: B2B enterprise – logistics, grocery, manufacturing, and other verticals requiring physical automation (currently testing with a small number of partners)
- **Mission**: “Bringing general-purpose AI into the physical world” – developing learning algorithms and foundation models to power robots and other physically-actuated devices

## Products & Services
- **π0 (pi-zero)**: First generalist policy released in October 2024; a vision-language-action (VLA) model capable of dexterous multi-task robot control. Open-sourced in February 2025.
- **π0.5**: VLA with open-world generalization (April 2025); can control a mobile manipulator to clean unfamiliar kitchens or bedrooms.
- **π0.7**: Steerable robotic foundation model with emergent capabilities (April 2026); can control a new robot platform without additional training.
- **π*0.6**: VLA trained with reinforcement learning to improve success rate and throughput on real-world tasks (November 2025).
- **FAST**: Efficient robot action tokenizer enabling 5x faster training of generalist policies (January 2025).
- **Multi-Scale Embodied Memory (MEM)**: Gives models long- and short-term memory for tasks exceeding ten minutes (March 2026).
- All offerings are research-stage models; the company does not currently sell a commercial product but partners with select companies for testing.

## Market Standing
- **Valuation**: $5.6 billion (as of January 2026, per TechCrunch)
- **Total Funding**: $1.07 billion across four rounds:
  - Seed (March 2024): $70M led by Lux Capital and Thrive Capital
  - Series A (November 2024): $400M led by Lux Capital and Thrive Capital
  - Venture Round (November 2025): $600M from 8 investors
  - Venture Round (March 2026): undisclosed amount from 4 investors
- **Notable Investors/Partners**: Khosla Ventures, Lux Capital, Thrive Capital, Sequoia Capital, OpenAI, CapitalG, Redpoint Ventures, Bond
- **Growth Signals**: Headcount grew 183.5% year-over-year to 163 employees (LinkedIn, mid-2026); the company states it has “blown through” its original 5-10 year roadmap in just 18 months; test deployments in logistics, grocery, and food production.

## Competitive Advantages
- **Cross-embodiment learning**: Models can transfer knowledge to any new robot hardware without starting data collection from scratch, lowering the marginal cost of onboarding autonomy.
- **Pure research focus**: Unlike competitors (e.g., Skild AI), Physical Intelligence deliberately avoids near-term commercialization, allowing the team to pursue general intelligence without product pressure.
- **World-class founding team**: Combination of top robotics academics (Levine, Finn) and experienced entrepreneurs/operators (Groom, Hausman).
- **Open-source release**: π0 weights and code are publicly available, fostering community contributions and accelerating research.

## Strategic Focus
- Current priorities include scaling foundation models to more tasks and environments, improving generalization and robustness, and expanding partnerships for real-world testing.
- The company explicitly does not give investors a timeline for monetization; instead it focuses on building general-purpose physical intelligence with a 5-10 year horizon (though progress has been faster than expected).
- Future strategy centers on continuous improvement via a loop of data collection → training → evaluation → more data, rather than rapid deployment.

## Why Work Here
- **Culture**: Described as a “pure company” – internally driven by research needs, not external market demands. Highly collaborative, with a mix of engineers, scientists, and roboticists working together.
- **Work Environment**: Hybrid/in-office – most roles require on-site presence in San Francisco (396 Treat Ave), though some remote flexibility exists. In-office setting with a “no reception” vibe, open lab space with robot stations.
- **Growth**: Team has scaled from ~80 (Jan 2026) to 163 (mid-2026) and is still hiring across research, ML infra, hardware, and engineering roles. Plans to grow “as slowly as possible” to maintain quality.
- **Perks & Engineering Highlights**: Access to cutting-edge robotics hardware and compute resources; opportunity to publish research and open-source code; exposure to a wide variety of real-world automation challenges (e.g., robots learning to fold pants, peel vegetables, make espresso). Employees come from top institutions like Berkeley, Stanford, Google, NVIDIA, and Anduril.

## Sources
1. [physicalintelligence.company](https://www.physicalintelligence.company/) – Official website, model releases, and values
2. [TechCrunch](https://techcrunch.com/2026/01/30/physical-intelligence-stripe-veteran-lachy-grooms-latest-bet-is-building-silicon-valleys-buzziest-robot-brains/) – In-depth profile including valuation, strategy, and culture
3. [LinkedIn](https://www.linkedin.com/company/physical-intelligence) – Company details, headcount, funding, and talent sources
4. [Built In](https://builtin.com/company/physical-intelligence) – Career page, employee count, and office policy
5. [jobs.ashbyhq.com/physicalintelligence](https://jobs.ashbyhq.com/physicalintelligence) – Current job openings

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