Technical Product Manager

Genesis AI; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Genesis AI is seeking a Product Manager to own the roadmap for core Physical AI capabilities, translating research breakthroughs into deployable, customer-facing products.

You will sit at the intersection of research, robotics engineering, and field deployment to turn ambiguous tradeoffs into clear product decisions, and define readiness criteria for customer-site deployments.

Qualifications

• Shipping technical products with complex tradeoffs.
• Ability to read policy evaluations and discuss sim-to-real gaps.
• Bias toward field work over the whiteboard.
• Exceptional written specs and decision logs.
• Comfort with incomplete information in a fast-moving field.
• Bonus: robotics/autonomy experience.

Responsibilities

• Own the product roadmap for Physical AI capabilities, turning research breakthroughs into deployable products.
• Bridge research, robotics engineering, and field deployment to resolve tradeoffs.
• Define what is ready for customer sites by setting success metrics and reliability thresholds.
• Drive cross-functional alignment across distributed teams in research, engineering, and field operations.

Skills

Tradeoff management

Technical product sense

Field-focused mindset

Writing specs/logs

Robotics/autonomy familiarity

Job description

What You'll Do

• Own the product roadmap for our core Physical AI capabilities, translating research breakthroughs into deployable, customer-facing products.

• Sit at the intersection of research, robotics engineering, and field deployment to turn ambiguous technical tradeoffs into clear product decisions.

• Define what \"ready for a customer site\" actually means by setting success metrics, reliability thresholds, and scope boundaries for each release.

• Drive cross-functional alignment across distributed teams in research, engineering, and field operations.

What You'll Bring

• Track record of shipping technical products where the primary challenge was managing complex tradeoffs, not filling out roadmap slides.

• Deep enough technical understanding to read a policy evaluation, understand a sim-to-real gap, or participate in complex debug sessions and ask the right questions without needing to write the code yourself.

• Strong bias toward the field over the whiteboard, preferring to evaluate a failed pick on a live customer floor over reading ten synthetic benchmark reports.

• Exceptional written communication skills to write specs and decision logs that hold up when you're not in the room.

• Comfort operating with incomplete information in a fast-moving, pre-paradigm field where answers aren't obvious.

• Bonus: Prior experience in robotics, autonomy, or another domain where \"works in the lab\" and \"works in the world\" carry vastly different bars for success.