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# Senior Machine Learning Engineer, Reinforcement Learning

- **Company:** Path Robotics
- **Location:** Columbus, OH, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Python (Programming Language), Machine Learning, Motion Planning, Tensorflow, Robotic Automation Software, Reinforcement Learning, Pytorch, Transfer Learning, Deep Learning, Information Technology, Machine Learning Operations
- **Published:** June 17, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ce3c5152744a7937

## About the Role

Do you have a Master's degree?, * Master's or PhD in Computer Science, Robotics, Machine Learning, or related field, or equivalent practical experience.

 * Experience developing and deploying reinforcement learning algorithms on real-world systems.
 * Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
 * Experience with simulation environments (e.g., MuJoCo, Isaac Gym).
 * Solid understanding of probability, statistics, and optimization.
 * Experience with training and deploying ML models in production systems.

## Description

* Design, implement, and evaluate RL algorithms for robotic control, motion planning, and adaptive behaviors in dynamic, unstructured environments.
 * Develop and integrate RL policies with robot control systems, ensuring compatibility with hardware constraints and real-time requirements.
 * Collaborate with perception teams to fuse RL with vision, depth, and sensor data for robust decision-making.
 * Build and maintain sim-to-real pipelines, including domain randomization and transfer learning techniques.
 * Conduct experiments on physical robots, including designing safety protocols and monitoring for unexpected behaviors.
 * Leverage simulation environments (Isaac Gym, Gazebo, MuJoCo, PyBullet) for large-scale training before real-world validation.
 * Continuously improve model efficiency to operate within compute and latency constraints on embedded robotic systems., * Daily free lunch to keep you fueled and connected with the team


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