Senior Machine Learning Engineer - Reinforcement Learning

Path Robotics is tackling a trillion dollar opportunity in the robotics industry by addressing the shortage of skilled labor. The Senior Machine Learning Engineer will design, implement, and optimize reinforcement learning algorithms for robotic systems, collaborating with cross-functional teams to enhance performance in dynamic environments.

Responsibilities:

• 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

Requirements:

• 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