Perception Engineer

Show Map

• Location340 Shaw Rd, South San Francisco, CA, 94080, United States
• Base Pay$150,000.00 - $200,000.00 / Year
• Employee TypeExempt (FT)

Description About BurnBot Wildfire has stopped being a season. BurnBot builds the machines that get ahead of it — remotely operated systems that apply and contain prescribed fire, and platforms that clear heavy fuel on terrain that isn’t safe for crews.

Our fleet is at work today for PG&E, CAL FIRE, the U.S. Forest Service, Caltrans, fire districts, and tribal nations across California, Oregon, and Washington — treating land at up to 40x the pace of conventional methods. We’re roboticists, engineers, and career fire practitioners. Hardware we design in South San Francisco is in the dirt within weeks, and the people who designed it are usually standing next to it. THE ROLE Our machines have to see what a fire crew sees: where the fuel is, how heavy it is, where the ground drops away, where the fire line is, and where the people are. They have to do it through smoke, dust, glare, and at night.

You’ll own the perception stack that makes that possible — sensors, models, and the data engine behind them — on machines that work in real vegetation, not a parking lot. WHAT YOU’LL OWN

• The perception stack: camera, lidar, thermal, and radar — selection, placement, calibration, and fusion

• Detection and segmentation of vegetation, terrain, obstacles, fire, and people, tuned for the conditions our machines actually work in

• The data engine: what we collect in the field, how it gets labeled, and how quickly a failure becomes a training example

• Evaluation you trust. Real metrics on real field data, and the honesty to say when a model isn’t ready.

• Deployment onto embedded compute on the machine, within real latency and power budgets

Requirements WHAT YOU’LL BRING

• 5+ years building perception for robots or vehicles that operate outside a lab

• Strong C++ and Python

• Deep learning for detection and segmentation, and the judgment to know when classical methods are the better answer

• Multi-sensor calibration and fusion, and comfort with the geometry underneath it

• ROS or ROS 2, and the tooling around field data — bags, replay, visualization

• Field debugging instincts. You’ve chased a bug that only reproduced outdoors

• B.S. or higher in robotics, computer science, electrical engineering, or equivalent experience

NICE TO HAVE

• Thermal or IR imaging experience

• Lidar in vegetation — foliage penetration, ground segmentation, or point-cloud classification

• Off-road or unstructured-environment perception (agriculture, mining, forestry, defense)

• Active learning or data-engine tooling at scale

• Wildland fire, forestry, or land management background

Summary HOW WE WORK

• Based onsite in South San Francisco — design, build, and test all happen in one building, and being near the machines is most of the point

• Flexible within that. You own your calendar: work the hours where you’re sharpest, and go remote on heads-down days.

• Expect a few days a month in the field across California, Oregon, and Washington. Watching your work run on a live burn is the best part of the job.

COMPENSATION & BENEFITS Base salary: $150,000 – $200,000 — final offers reflect experience and demonstrated scope.

• Equity — Incentive Stock Options

• Health, dental, and vision

• Flexible paid time off

Still interested? Please apply by visiting BurnBot.com/Careers, or by sending your resume to [email protected].

Burnbot is an Equal Opportunity Employer and does not discriminate based upon race, religion, color, national origin, sex (including but not limited to, pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with one or more disabilities, or other applicable legally protected characteristics.

If you need assistance or accommodation due to a disability, you may contact us at (415) 795-9124 x 1010 or [email protected].