Senior Machine Learning Engineer - Reinforcement Learning

Path Robotics is tackling a trillion dollar opportunity in the robotics industry by addressing the skills gap with innovative solutions. As a Senior Machine Learning Engineer focused on Reinforcement Learning, you will design and optimize RL 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