Founding Machine Learning - World Models
San Francisco, CAFull-timePosted 3w agoStill listed today
Most applications go out cold — see where you stand first. No sign-up to start.
You apply on the employer's site, with no Olive account needed.
Watch jobs like this. New roles like this one near San Francisco, CA, by email.
Don't just apply. Show up ready.
Olive works from this exact posting.
At a glance
Olive lists jobs from US employers, including remote roles you can work from the United States.
Job overview
One Robot builds world models that simulate manipulation scenes to validate policies and potentially train them without using a robot. The founding machine learning role develops generative models with action conditioning, controllability, and physical fidelity. The work includes improving long-horizon rollout quality, operating multi-GPU training infrastructure, and building a data engine for learning across customers and manipulation tasks.
Skills & qualifications
Skills
Qualifications
Full job description
We build world models that simulate manipulation scenes faithfully enough to validate, and one day, train policies without touching a robot. You'll develop generative models that make this work, with the controllability and physical fidelity to match real-robot behavior. What you'll do:
-
Train video and dynamics models: Develop world models with action conditioning for manipulation policies.
-
Push long-horizon coherence: Develop architectures and training methods that extend rollout quality on hard physical tasks.
-
Own training infrastructure: Run multi-GPU clusters, write custom CUDA, debug at scale.
-
Build the world-model data engine: Design, implement, and improve a data engine that allows the world model to compound learning across customers and manipulation tasks.
Requirements:
-
Very strong coding in Python and PyTorch (or similar).
-
Video generation experience: Deep experience training image or video generation models end-to-end.
-
Large-scale training: Track record operating training runs at cluster scale.
-
3D vision: Working knowledge of multi-view geometry, scene reconstruction, and physical priors.
How this job compares
Set against the 2,110 open Machine Learning jobs on Olive Jobs, counted November 5, 2026.
- Pay
- This postingNot listed
- California median$193–283K/yr336 salary ranges
- California median$54–70/hr31 hourly ranges
- Openings
- Olive Jobs lists 486 open Machine Learning jobs in California and 2,110 across the US. 7% of them nationwide are listed as remote or flexible.
- Experience
- Machine Learning postings that state a minimum ask for 5 years of experience at the median; the middle half ask for 3 to 8 years (1,590 postings).
- Education
- 786 of the 2,110 open Machine Learning jobs (37%) 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.
Prepare for this role
You've read the whole posting — now see how you match it.
