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Principal Physical Systems Architect

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: DeepRec.ai
Full Time position
Listed on 2025-12-28
Job specializations:
  • Engineering
    Robotics, Systems Engineer, Automation Engineering, Electrical Engineering
Salary/Wage Range or Industry Benchmark: 250000 USD Yearly USD 250000.00 YEAR
Job Description & How to Apply Below

Base pay range

$/yr - $/yr

Co-Founder , Recruiting Top GenAI, LLM, Computer Vision and Robotics Talent

Principal Physical Systems, Robotics & Manufacturing Architect

Location: Bay Area (or equivalent manufacturing hub)

Level: Senior Principal / Distinguished Engineer (IC-first, light people leadership)

Role Summary

We are looking for a deeply technical, hands‑on engineer who understands how complex physical systems are actually built, scaled, and operated — and who can connect that understanding to modern robotics and AI systems.

You will act as a technical anchor for the company’s physical reality — ensuring that what we design can be built, calibrated, tested, and scaled in real industrial environments.

This is not an executive role and not a pure research role.

It is for someone who has personally shipped machines and understands why things fail when they leave the lab.

What You Will Do Own Physical Reality Across the Stack
  • Serve as a principal architect for physical systems spanning:
  • Robotics and automation
  • Sensors, actuators, electronics, and embedded controllers
  • Firmware, real‑time systems, and controls
  • Manufacturing processes, tooling, and test infrastructure
  • Be the person who can reason end‑to‑end, from firmware timing constraints to factory yield curves.
Bridge Robotics, AI, and Manufacturing
  • Partner closely with autonomy and AI teams to ensure:
  • ML/RL/VLM‑based systems respect real‑time, safety, and physical constraints
  • Data collection, simulation, and evaluation reflect manufacturing and field realities
  • Translate autonomy and learning requirements into buildable hardware and process decisions.
Deep Manufacturing & Process Insight
  • Bring hands‑on experience in serious manufacturing or esoteric physical environments, such as:
  • Semiconductor tools or factory systems
  • Precision optics, lasers, plasma, vacuum, or metrology
  • High‑throughput robotic automation or complex production lines
  • Identify failure modes related to tolerances, drift, wear, contamination, calibration, and process variability.
Hands‑On Technical Leadership
  • Be deeply involved in:
  • Design and architecture reviews
  • Prototype bring‑up and system integration
  • Failure analysis, root‑cause investigations, and corrective actions
  • Set the technical bar through credibility and experience, not hierarchy.
Raise the Organization’s Physical Systems IQ
  • Mentor engineers across hardware, robotics, and autonomy on how systems behave at scale.
  • Help the team internalize what will and will not scale, long before it becomes a problem.
  • Establish norms around engineering rigor, test discipline, and physical intuition.
What We’re Looking For Required Experience
  • 10–15+ years building complex physical systems that integrate hardware, software, and automation.
  • Demonstrated experience in industry‑scale manufacturing environments or deeply technical physical processes.
  • Strong understanding of embedded systems, firmware, and real‑time control.
  • Working fluency with robotics autonomy concepts, including perception, planning, and learning‑based systems.
  • Track record of taking systems from prototype → pilot → scaled deployment.
Strong Signals (One or More)
  • Built or scaled semiconductor tools, factory automation, or advanced manufacturing equipment.
  • Worked on robotic systems deployed in production, not just lab demos.
  • Known for being able to debug problems that cross firmware, hardware, robotics, and process boundaries.
  • Comfortable challenging AI/ML assumptions when they conflict with physical or manufacturing reality.
Bonus (Differentiators)
  • Experience with digital twins, HIL, or sim‑to‑real tied to real manufacturing data.
  • Exposure to ML/RL/VLMs in embodied or physical systems contexts.
  • Patents or technical contributions grounded in real machines or processes.
Seniority Level

Seniority Level: Mid‑Senior

Employment type
  • Full‑time
Job function
  • Information Technology
Industries
  • Technology, Information and Media
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