# Robot Learning Engineer - Manipulation at Applied Intuition

- Company: Applied Intuition
- What the company does: Applied Intuition powers physical AI, automating machines across automotive, defense, trucking, mining, construction, & agriculture. Backed by General Catalyst, Kleiner Perkins and a16z.
- Company website: https://www.appliedintuition.com/
- Type: Startups (AI role)
- Level: Mid level
- Location: Sunnyvale
- Work setup: On-site
- Pay: $150K to $300K base salary per year (USD)
- Posted: 2026-09-21
- Apply by: 2026-11-05
- Apply: https://jobs.ashbyhq.com/Applied/ef7fb9ed-e254-4b90-aef2-efa9c30e7cd8
- Page: https://www.1752.vc/careers/jobs/applied-intuition-robot-learning-engineer-manipulation/

## About the role

Applied Intuition is building a robot learning platform on Dana, its physical AI platform: the data infrastructure and training intelligence a company needs to make any robot learn an industrial task and keep improving it. The robotics team builds that platform and uses it to deliver robot autonomy on customer lines, training, evaluating, and deploying policies on real robots doing real industrial tasks. Everyone on the team works hands-on with hardware and sees their work reach customers.

## What they're looking for

- Trained or fine-tuned a learned manipulation policy and deployed and evaluated it on a physical robot
- Strong Python and PyTorch skills, with the ability to write maintainable training, evaluation, and deployment code
- Practical depth in imitation learning and at least one modern policy family, such as vision-language-action models, diffusion policies, or action-chunking transformers
- Working knowledge of robot kinematics, coordinate frames, camera calibration, and the interface between learned actions and low-level control
- The habit of diagnosing failures with controlled experiments across data, sensing, model, and execution
- Comfort taking on open-ended problems and communicating tradeoffs clearly to teammates at the robot

Tags: Robotics