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Robot Learning Engineer - Manipulation

appliedSunnyvaleRobotics
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Salary
$150K – $300K
Job type
Full-time
Experience
Mid · 1+ yrs
Posted
21 Sept 2026
Status
Open · checked 7d ago

About this role

The Robot Learning Engineer - Manipulation position at Applied Intuition involves building and deploying manipulation policies on physical robots in Sunnyvale. This opportunity suits professionals with practical experience in robot learning who want to work hands-on with hardware in an in-office environment.

Role Overview

Applied Intuition is seeking a Robot Learning Engineer to join its robotics team in Sunnyvale. The selected candidate will handle manipulation policies from initial task definition to reliable execution on physical robots. Responsibilities include training models, investigating failures, and ensuring system dependability for customer applications.

Key Responsibilities

Manage the complete learning loop for manipulation tasks, covering task definition, demonstration collection, data curation, training, real-robot evaluation, and deployment.
Train and fine-tune various manipulation policies, ranging from large pretrained models to compact task-specific alternatives.
Formulate repeatable recipes for pick-and-place, bimanual handling, and contact-rich assembly tasks incorporating force or tactile signals.
Deploy policies onto edge compute hardware while validating observation processing, action interfaces, and control timing.
Convert operational failures and human interventions into improved data, models, and evaluation frameworks.
Track customer metrics like success rates, cycle times, and intervention frequencies to continuously improve task performance.

Requirements

Minimum of 1 year of professional experience.
Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience.
Demonstrated background in training, fine-tuning, deploying, and evaluating learned manipulation policies on physical hardware.
Proficiency in Python and PyTorch for writing maintainable code.
Practical familiarity with imitation learning alongside policy families such as vision-language-action models, diffusion policies, or action-chunking transformers.
Understanding of robot kinematics, coordinate frames, camera calibration, and low-level control interfaces.

Nice to Have

Experience working with bimanual manipulation, force-controlled insertion, tactile sensing, or dexterous hands.
Familiarity with ROS 2, LeRobot, or simulators like Isaac and MuJoCo.
Background in optimizing inference on NVIDIA Jetson or GPU edge systems through export, compilation, or quantization.
Experience involving reinforcement learning post-training, learning from interventions, or cross-platform policy transfer.

Skills and Tools

Python
PyTorch
ROS 2
LeRobot
Isaac
MuJoCo
NVIDIA Jetson

Salary and Benefits

Base salary range spanning $150K to $300K.
Equity options and restricted stock units.
Comprehensive health, dental, vision, life, and disability insurance coverage.
401(k) retirement plan with an employer match.
Learning and wellness stipends alongside paid time off.

About the Company

Applied Intuition powers physical AI by creating digital infrastructure for moving machines across automotive, defense, trucking, construction, mining, and agriculture sectors. Founded in 2017 and headquartered in Sunnyvale, California, the organization operates additional offices internationally and domestically.

How to Apply

To apply for this position, please visit the official company careers page.

Skills and tech stack

PythonPyTorchROS 2LeRobotIsaacMuJoCoNVIDIA JetsonTransformersReinforcement LearningDiffusion

Questions candidates ask

What is the location and work arrangement for this role?

The role is located in Sunnyvale, California. Employees are expected to primarily work from the office 5 days a week, with some flexibility for occasional remote work or schedule management.

What is the salary range for the Robot Learning Engineer position?

The intended base salary ranges from $150K to $300K, supplemented by equity offerings.

What educational background is required?

A Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience is required.

How many years of professional experience are needed?

Candidates must have 1 or more years of professional experience.

What technologies and frameworks are expected?

Candidates need strong skills in Python and PyTorch, along with practical experience in imitation learning and modern policy families like vision-language-action models, diffusion policies, or action-chunking transformers.

Ready to apply?

The application is on the official applied careers page.

Apply on company site