Robot Learning Engineer - Manipulation

• Work on the full learning loop for manipulation tasks: task definition, demonstration collection, data curation, training, real-robot evaluation, and deployment.

• Train and fine-tune manipulation policies, from large pretrained models such as vision-language-action models to compact task-specific policies, and choose the right approach for each task.

• Develop repeatable recipes for industrial tasks such as pick-and-place, bimanual handling, and contact-rich assembly, adding force or tactile signals where they help.

• Deploy policies on edge compute and validate observation processing, action interfaces, and control timing on the robot.

• Turn failures and human interventions into better data, better models, and better evaluation.

• Measure what customers care about, including success rate, cycle time, intervention rate, and the data and time needed to reach a target, and improve those numbers task after task.

• Package recipes and models so the next task, and the next robot, starts from what was learned on the last one.

• 1+ years of professional experience

• A Bachelor's degree in Computer Science, Software Engineering, or equivalent

• 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.

• Experience with bimanual manipulation, force-controlled insertion, tactile sensing, or dexterous hands.

• Experience with ROS 2, LeRobot, or simulators such as Isaac and MuJoCo.

• Experience optimizing inference on NVIDIA Jetson or GPU edge systems, including model export, compilation, or quantization.

• Experience with reinforcement learning post-training, learning from interventions, or transferring policies across robot platforms.

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment. Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position. Don't meet every single requirement? If you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.