---
title: 'Prototype Engineer at Physical Intelligence'
canonical: 'https://feeny.ai/job/prototype-engineer-physical-intelligence-san-francisco-2ttjzz5d850r'
type: 'job'
last_seen: '2026-09-06'
---

# Prototype Engineer at Physical Intelligence

- **Company:** Physical Intelligence
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-07-24
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/physicalintelligence/17107519-0e50-430a-b742-200f08388d29

## Job description

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.

We're looking for a Prototype Engineer, an engineering generalist who sits at the intersection of enabling research and deloying into real-world applications. You'll work closely with our research and engineering teams to rapidly design, build, and iterate on concept mechanical, electrical, and sensor prototypes that push the boundaries of what our robots can do.

This role is uniquely positioned between R&D and hardware engineering. You'll translate research ideas into physical systems, build end-to-end prototypes from scratch, and ensure our hardware performs reliably when interacting with real-world objects. You're the person both the hardware team and researchers come to when they need something built and rapidly iterated on. When successful, you'll be responsible for turning these into scalable solutions that support multiple hardware platforms in our fleet.

In this role you will

- Rapidly design and fabricate mechanical, electrical, and sensor prototypes to support research experiments and engineering development.
- Partner directly with researchers to understand experimental requirements and translate them into buildable hardware systems.
- Build end-to-end prototype systems: from concept sketches through CAD, fabrication, wiring, sensor integration, and validation.
- Develop quick-turn PCBs, wiring harnesses, and cable assemblies for prototype electronics.
- Evaluate and select sensors, actuators, and off-the-shelf components for integration into prototype systems.
- Design and iterate on fixtures, jigs, test rigs, and custom tooling to enable research workflows.
- Perform hands-on assembly, troubleshooting, and debugging of electromechanical and robotic systems.
- Collaborate with electrical and robot software engineers to integrate hardware with control systems, firmware, and runtime software.
- Identify and address failure modes specific to hardware operating in unstructured, real-world environments (contact forces, wear, thermal effects, cable management, etc.).
- Document designs, test results, and build procedures to support knowledge transfer and design iteration.

## What we hope you'll bring

- Bachelor's degree in Mechanical, Electrical or Mechatronics Engineering, or a related field.
- 2-5 years of experience in prototyping, R&D engineering, or hardware development, ideally preferably in robotics, automotive, consumer electronics, or research lab environments.
- Proficiency in CAD software (Onshape, SolidWorks, or Fusion 360) with strong 3D modeling and drafting skills.
- Working knowledge of PCB design, electronics and comfortable soldering, wiring, reading schematics, and integrating sensors (force/torque, IMUs, cameras, encoders, etc.).
- Hands-on expertise with rapid prototyping methods: 3D printing (FDM/SLA), laser cutting, CNC machining, sheet metal fabrication, and manual machining.
- Familiarity with the robotics domain, with an understanding of kinematics, actuation, compliant mechanisms, and the challenges of hardware interacting with unstructured real-world environments.
- Ability to build full first-pass systems end-to-end, from mechanical structure through electrical integration to basic software scripting.
- Strong communication skills, with the ability to speak the language of both researchers and engineers. Translating abstract research needs or engineering requests into tangible concepts.
- Comfort working in a fast-paced, ambiguous environment where requirements evolve quickly and scrappiness is valued.
- Experience with basic scripting (Python) for test automation, data collection, or hardware interfacing is a plus.

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

## Other roles at Physical Intelligence

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- [Software Engineer, Data Quality](https://feeny.ai/job/software-engineer-data-quality-physical-intelligence-san-francisco-p7f1n4g3j35e) — San Francisco, CA
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- [Fullstack Software Engineer](https://feeny.ai/job/fullstack-software-engineer-physical-intelligence-san-francisco-4d81qeq8e7hy) — San Francisco, CA
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