# Forward Deployed Robotics Engineer at Physical Intelligence

> Onsite · United States · Unspecified · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3Aphysicalintelligence%3A567d620f-7600-4e35-9edd-f41ed4db45ce (read 2026-11-05).

## Facts (observed)

- Company: [Physical Intelligence](https://alderhq.app/companies/physical-intelligence)
- Location text: San Francisco
- Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco")
- Posted: 2025-11-17 (353 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/physicalintelligence/567d620f-7600-4e35-9edd-f41ed4db45ce
- Skills listed (inferred): Python

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (SF Bay Area, n 1495): p25 $161k, median $200k, p75 $247k
- H-1B filings at this company for similar roles, FY26: 3, median offered wage $188k ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance))

## Description (the employer's text)

### Role Overview

As a Forward Deployed Robotics Engineer, you'll serve as the first line of technical defense for our growing fleet of robotic systems deployed across warehouse and external data-collection environments. Our diverse robot fleet—including both static and mobile systems—performs complex manipulation and sensing tasks in real-world settings. When issues arise, you'll be the first responder: analyzing field tickets, reproducing issues, gathering diagnostic data, and driving resolution to ensure maximum fleet uptime.

### Key Responsibilities

- Primary Robot Fleet Issue Technical Triage Point: Manage incoming fleet issue ticket queue, prioritize based on fleet-wide implications and operational goals, and triage as hardware, software, or operational issue.

- Fast-Paced Operations: Handle quick turnaround expectations while maintaining diagnostic quality

- On-Site Diagnostics: Perform physical inspections and functional tests at robot stations to verify issue reproduction

- Data Analysis: Analyze telemetry, sensor data, and logs to form and test hypotheses about root causes

- Failure Analysis: Execute technically sound Failure Analysis / Root Cause Analysis procedures

- Cross-Team Collaboration: Partner with hardware and software teams to reproduce and resolve complex issues

- Pattern Recognition: Identify recurring issues across the fleet and surface reliability insights for design improvements

- Documentation: Maintain clear, traceable documentation for every diagnostic and escalation event

- Metrics & Reporting: Track and report issue trends and fleet health metrics to leadership

- Process Improvement: Collaborate with team lead to develop and maintain diagnostic procedures and troubleshooting guides

### Required Competencies & Skills

- Education: B.S. in Robotics, Mechatronics, Systems Engineering, or equivalent experience

- Hardware Knowledge: Proficiency debugging electromechanical systems including actuators, PCBs, cameras, wiring harnesses, and communication hardware

- Software Knowledge: Experience with log parsing and basic scripting for diagnostics (Python or Bash)

- Systems Knowledge: Strong understanding of mechanical, electrical, and software interactions in robotic systems

- Communication: Excellent written and verbal communication, particularly in technical documentation and shift handoffs

- Hands-On Problem Solving Experience: Minimum 2 years work experience with debugging and completing root cause investigations of systems with hardware and software issues

### Strongly Preferred

Experience supporting multi-robot fleets, warehouse automation systems, or field robotics deployments

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

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Aphysicalintelligence%3A567d620f-7600-4e35-9edd-f41ed4db45ce and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.