---
title: 'Mechanical Design Engineer at Physical Intelligence'
canonical: 'https://feeny.ai/job/mechanical-design-engineer-physical-intelligence-san-francisco-bem86pfx2paz'
type: 'job'
last_seen: '2026-11-01'
---

# Mechanical Design Engineer at Physical Intelligence

- **Company:** Physical Intelligence
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-06-14
- **Last confirmed live:** 2026-11-01
- **Apply:** https://jobs.ashbyhq.com/physicalintelligence/58e5a454-47db-41b2-9c5d-c8e34c55159e/application

**Skills:** 3D CAD, 2D drawings, Material selection, Manufacturing processes, Injection molding, Die casting, Stamping, Machining, Bonding methods, FEA tools, HALT/HASS, FMEA, DOE methodologies, Sheet metal fabrication, 3D printing, Prototyping, Reliability testing, EMI analysis, Thermal analysis, Structural analysis

> Drive the integration and development of robotic systems by owning the full mechanical development spectrum from concept to deployment. The role involves leading innovative designs, optimizing manufacturing processes, ensuring reliability, and collaborating with cross-functional teams to produce high-volume producti...

## Job description

We're looking for an experienced mechanical engineer to drive the integration and development of our robotic systems, leading innovative designs from concept to deployment. You'll own the full spectrum of mechanical development—from actuator sizing or design to kinematics and work with teams to prototype and ultimately produce systems at scale—ensuring reliability, deployability, and performance. The ideal candidate is a hands-on innovator with deep expertise in mechatronic systems, combining theoretical knowledge with practical engineering skills. Experience with actuation systems, electromechanical integration, machine design, and a track record of bringing mechanical systems to life is essential. If this sounds like you, please apply!

In This Role You Will

- Own the mechanical design lifecycle: Drive all design decisions around 3D CAD, 2D drawings, material selection, and manufacturability — from early concept and proof-of-concept prototypes through high-volume production.
- Develop and refine manufacturing processes: Identify and optimize injection molding, die casting, stamping, machining, adhesives, and bonding methods for new and existing products.
- Ensure reliability and robustness: Perform and interpret reliability tests (HALT/HASS, tolerance stack-ups, environmental testing) and lead corrective design actions.
- Leverage simulation for smart decisions: Use basic FEA tools (thermal, structural, vibrational) and first-order analyses to validate or guide design from early phases onward.
- Lead system integration efforts: Collaborate with electrical and radio teams to balance thermal, EMI, mechanical stability, and accessibility needs in tightly integrated assemblies.
- Prototype and iterate quickly: Build proof-of-concept designs, run experiments, and translate findings into high-yield, mass-production-ready solutions.
- Manage vendor relationships: Evaluate DFM, cost, yield, and timeline trade-offs; work with JDM/CM/ODM partners; own and drive supplier selection where needed.
- Communicate effectively across teams: Conduct design reviews with cross-functional stakeholders, clearly articulating design rationale, risks, and trade-offs.

## What We Hope You'll Bring

- 7+ years of experience taking hardware products from concept to production, with a strong portfolio of shipped mechanical designs — preferably in robotics, automotive, or consumer products
- Bachelor's Degree in Mechanical or Aerospace Engineering, or equivalent experience
- Deep understanding of high-volume manufacturing processes (injection molding, die casting, stamping, machining, bonding)
- Familiarity with HALT/HASS, FMEA, DOE methodologies, and test-to-failure approaches for robust mechanical design
- Practical understanding of when and how to apply FEA tools, with the ability to make first-order engineering judgments
- Proven record of mechanically integrating electronics (sensors, PCBs, antennas, batteries) in complex assemblies
- Ability to lead reviews, influence cross-functional teams, and convey risks and solutions clearly
- Comfort in early-stage, resource-limited startup environments with a willingness to move quickly and hands-on
- Proficiency in prototyping methods including machining (mill, lathe), sheet metal fabrication, 3D printing, and injection molding
- Experience building and testing prototypes and analyzing failures to implement improvements

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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