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# Machine Learning Engineer, Robot Learning

- **Company:** Path Robotics
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** C++ (Programming Language), Computer Programming, Python (Programming Language), Machine Learning, Robotic Automation Software, Reinforcement Learning, Information Technology
- **Published:** June 9, 2026
- **Apply:** https://www.dice.com/job-detail/51bce006-1f60-4d56-90c6-f0d839399a9b

## About the Role

* Ph.D. or Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
 * Proven track record in publishing at top conferences (e.g., NeurIPS, ICLR, ICML, CoRL, RLC).
 * Experience with robotic simulation tools (e.g., Isaac Sim, MuJoCo).
 * Experience with machine learning techniques applied to robot manipulation.
 * Experience building models from scratch and deploying them in real-world applications.
 * Experience with pose estimation, segmentation, active perception, and affordance-based bin picking.
 * Strong programming skills in languages such as C++ or Python.
 * Experience with robotic simulation tools (e.g., Isaac Sim, MuJoCo).
 * Proven track record of deploying scalable solutions for autonomous robotic systems.
 * Strong communication skills, with the ability to convey complex technical concepts to a diverse audience.

## Description

We are seeking a skilled and motivated Machine Learning Engineer with expertise in modern robotics and manipulation to join our Robot Learning team to build agentic AI systems for industrial applications. The ideal candidate will have experience in robotics, with a focus on developing and implementing advanced manipulation techniques, motion control systems, and planning algorithms for autonomous robots. This role involves working closely with cross-functional teams to design, test, and deploy innovative solutions that improve the performance and capabilities of our robotic systems.
What You'll Do

 * Work on the development and deployment of behavioral cloning (BC), reinforcement learning (RL), and diffusion models to solve complex robotic tasks.
 * Leverage multi-modal data, including image-based data, force, and torque to enhance robotic manipulation and control.
 * Design and implement vision-language-action (VLA) models for more intelligent and responsive robotic systems.
 * Craft strategies for the entire solution's lifecycle, including data collection, fleet learning, and continuous learning.
 * Develop, optimize, and deploy learning-based methods for robot control and object manipulation algorithms on a fleet of industrial robotic cells.
 * Collaborate with hardware and software teams to integrate manipulation, control, and planning algorithms into robotic platforms.
 * Stay updated with the latest advancements in robotics, control theory, and planning algorithms., * Daily free lunch to keep you fueled and connected with the team


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