Robot Learning Engineer Manipulation
Applied Intuition is a physical-AI company that provides software platforms for developing, validating, deploying, and operating intelligent vehicles and machines.
About Applied Intuition
Founded in 2017, Applied Intuition builds physical-AI tooling and infrastructure, a Vehicle OS, and a Self-Driving System for automotive, defense, trucking, construction, mining, agriculture, and robotics applications.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will own the learning loop for manipulation tasks, from task definition and data collection through training, real-robot evaluation, and deployment. You will diagnose failures, improve policies and data, measure customer outcomes, and package reusable models and recipes.
Requirements
- 1+ years of professional experience
- Bachelor's degree in Computer Science, Software Engineering, or equivalent
- Experience training, deploying, and evaluating learned manipulation policies on physical robots
- Python
- PyTorch
- Imitation learning
- Experience with a modern policy family
- Knowledge of robot kinematics, coordinate frames, camera calibration, and low-level control
- Experience diagnosing failures through controlled experiments
- Ability to communicate technical tradeoffs
Responsibilities
- Develop the full learning loop for manipulation tasks
- Train and fine-tune manipulation policies
- Develop repeatable recipes for industrial manipulation tasks
- Deploy policies on edge compute and validate robot interfaces
- Turn failures and human interventions into improved data and models
- Measure and improve success rate, cycle time, intervention rate, and learning efficiency
- Package models and recipes for reuse across tasks and robots
Benefits
- Equity
- Health insurance
- Dental insurance
- Vision insurance
- Life insurance
- Disability insurance
- 401k with employer match
- Learning stipend
- Wellness stipend
- Paid time off