Founding Machine Learning - Eval Layer

• One Robot builds task-specific world models and an evaluation platform for robot manipulation policies.
• Robotics can't industrialize without an evaluation layer. We're building it.
• 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 building the evaluation layer to understand policy failure modes before they hit production. You'll own modeling work that makes the eval trustworthy.
• Train evaluation models: Develop VLMs that classify and verify policy behavior.
• Build confidence layers: Convert model outputs into trustworthy signals the customer can act on.
• Improve model grounding: Make the eval models reason accurately about physical and spatial scenes.
• Build a self-improving eval layer: Develop data engine that makes the eval models sharper with each customer's deployments and corrections.
• Very strong coding in Python and PyTorch.
• VLM/LLM training: Track record in training VLMs or LLMs.
• Evals experience: Developed and shipped evals for VLMs or LLMs.

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