Founding Robot Learning
San Francisco, CAFull-timePosted 3w agoStill listed today
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At a glance
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Job overview
One Robot builds task-specific world models and an evaluation platform for robot manipulation policies. The founding robot learning role will train manipulation policies, validate the world model through simulation and real-hardware deployment, and build infrastructure for policy training and improvement. The company is based in San Francisco and works with customer data, real failures, and deployment pressure.
Skills & qualifications
Skills
Qualifications
Full job description
One Robot builds task-specific world models and an evaluation platform for robot manipulation policies. Training end-to-end policies for robots is vibes-based today. Teams collect data, train, deploy on a real robot, find out what fails, collect more, retry. We replace the trial-and-error with rigorous validation that tells you where your policy will fail and what data to collect to fix it. Robotics can't industrialize without an evaluation layer. We're building it. We're solving challenging technical problems around long-horizon autoregressive generation, world model controllability, and closing the sim-to-real gap. We work with real customer data, real failures, and real deployment pressure. We're based in San Francisco, backed by Accel, YC, several exited founders, and engineering leaders at leading AI companies. We're small and deliberately so. Everyone is an IC with deep ownership of a wide surface area. The culture is fast iteration and direct responsibility. Hemanth Sarabu and Elton Shon co-founded One Robot after leading robot learning together at Industrial Next (YC W22), bringing experience from Google, NASA JPL, and Tesla. We're expanding the platform into policy training — building the components that let policies validate and improve through our world model. You'll train manipulation policies — VLAs, end-to-end imitation, RL — and push the world model and eval forward. What you'll do:
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Train manipulation policies: Build VLAs, diffusion policies, or end-to-end imitation models and run them on real robots.
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Validate the world model end-to-end: Train policies in simulation, deploy on real hardware, and find what doesn't transfer.
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Push policy capabilities forward: Build the infrastructure that lets policies train and improve on our platform.
Requirements:
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Very strong coding in Python and PyTorch.
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Real-robot policy training: Track record training manipulation policies that ran on physical hardware.
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Demonstration data: Hands-on experience curating real-robot demonstration datasets.
How this job compares
Set against the 1,228 open Robotics Engineer jobs on Olive Jobs, counted November 5, 2026.
- Pay
- This postingNot listed
- California median$150–225K/yr327 salary ranges
- US median$42–45/hr31 hourly ranges
- Openings
- Olive Jobs lists 464 open Robotics Engineer jobs in California and 1,228 across the US. 2% of them nationwide are listed as remote or flexible.
- Experience
- Robotics Engineer postings that state a minimum ask for 4 years of experience at the median; the middle half ask for 3 to 5 years (890 postings).
- Education
- 503 of the 1,228 open Robotics Engineer jobs (41%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 5, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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