---
title: 'Robot Build Technician at Physical Intelligence'
canonical: 'https://feeny.ai/job/robot-build-technician-physical-intelligence-fremont-pzzwkp2xj9gk'
type: 'job'
last_seen: '2026-11-08'
---

# Robot Build Technician at Physical Intelligence

- **Company:** Physical Intelligence
- **Location:** Fremont, CA
- **Employment:** full-time
- **Posted:** 2026-02-16
- **Last confirmed live:** 2026-11-08
- **Apply:** https://jobs.ashbyhq.com/physicalintelligence/52fb2d63-f18e-446e-8a15-cbcdc8740147/application

**Skills:** Mechanical assembly, Electromechanical assembly, Robotics, Hand tools, Power tools, Soldering, Crimping, Torque wrenches, Cable harnessing, Wire routing, Electrical integration, Reading mechanical drawings, Reading schematics, Inventory management, Notion, Excel, PLCs, Automated equipment, CAN bus, Ethernet

> The Robot Build Technician builds, assembles, and maintains robotic systems for data collection and model training operations. This role involves working with the Hardware Engineering team to bring robots from prototype to production, ensuring quality and reliability through rigorous testing and documentation.

## Job description

We're looking for a hands-on Build Technician who thrives in a fast-paced hardware environment. You'll be responsible for building, assembling, and maintaining the robotic systems that power our data collection and model training operations. You'll work directly with our Hardware Engineering team to bring robots from prototype to production, ensuring quality and reliability at every step. What You'll Do:

- Build and assemble robotic systems according to engineering specifications, including mechanical, electrical, and electromechanical components
- Install, calibrate, and configure robots and end-of-arm tooling for various applications
- Execute test protocols and quality checks to ensure robots function as designed
- Maintain detailed service records and documentation for robotic equipment
- Support hardware bring-up, including wiring, harnessing, and integration of sensors and actuators
- Collaborate with mechanical, electrical, and software engineers to root-cause manufacturing issues and implement solutions
- Manage inventory of parts, tools, and consumables for the hardware lab
- Train team members on assembly procedures and best practices Competencies and Skills:
- 2+ years of experience in mechanical or electromechanical assembly, robotics, or manufacturing environments
- Proficiency with hand tools, power tools, and lab equipment (soldering, crimping, torque wrenches)
- Experience with cable harnessing, wire routing, and electrical integration
- Ability to read and interpret mechanical drawings, schematics, and assembly instructions
- Familiarity with robotic systems, PLCs, or automated equipment is a plus
- Basic understanding of CAN bus, Ethernet, and communication protocols
- Strong troubleshooting skills and attention to detail
- Comfortable working in a fast-paced, iterative environment
- Experience with inventory management and documentation tools (Notion, Excel)
- Prior experience in robotics, automotive, aerospace, or consumer electronics is highly valued

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

- [Deployment & Engagement Operations Lead](https://feeny.ai/job/deployment-engagement-operations-lead-physical-intelligence-san-francisco-rm51qjgc5bnt) — San Francisco, CA
- [Lead Security Engineer](https://feeny.ai/job/lead-security-engineer-physical-intelligence-san-francisco-c8snwvgksgkh) — San Francisco, CA
- [Environment Coordinator](https://feeny.ai/job/environment-coordinator-physical-intelligence-san-francisco-4gkxdz41bq8g) — San Francisco, CA
- [Environment Specialist](https://feeny.ai/job/environment-specialist-physical-intelligence-san-francisco-pc9emcb2qsb0) — San Francisco, CA
- [Environment Manager](https://feeny.ai/job/environment-manager-physical-intelligence-san-francisco-qdqkwxnvkkeg) — San Francisco, CA
- [Learning & Development Lead, Operations](https://feeny.ai/job/learning-development-lead-operations-physical-intelligence-san-francisco-rjw9n41fwmh4) — San Francisco, CA
- [General Manager, Research Operations](https://feeny.ai/job/general-manager-research-operations-physical-intelligence-san-francisco-t2n6gysx5vvr) — San Francisco, CA
- [Recruiter, Hardware](https://feeny.ai/job/recruiter-hardware-physical-intelligence-san-francisco-4n292t91sd6v) — San Francisco, CA
- [Set Team Specialist](https://feeny.ai/job/set-team-specialist-physical-intelligence-san-francisco-a1zm1e3dtf2d) — San Francisco, CA
- [ML Engineer, Platform](https://feeny.ai/job/ml-engineer-platform-physical-intelligence-san-francisco-9rgmerynps3m) — San Francisco, CA