Path Robotics develops AI-based systems that allow robots to learn, adapt, and operate in real-world settings, aiming to address gaps in skilled labor and transform industries. The company combines perception, reasoning, and control to produce practical AI that is risk-aware, reliable, and continuously improving through real-world usage. This Senior Machine Learning Engineer position focusing on Reinforcement Learning involves designing, implementing, and optimizing reinforcement learning algorithms that allow intelligent agents to function in dynamic, unstructured settings. The position requires close collaboration with cross-functional teams to design, test, and deploy solutions that enhance the performance and capabilities of robotic systems. The role is available at the Columbus, Ohio Headquarters or on a remote basis. Responsibilities include designing, implementing, and evaluating reinforcement learning algorithms for robotic control, motion planning, and adaptive behavior in dynamic, unstructured environments; developing and integrating RL policies with robot control systems while ensuring compatibility with hardware constraints and real-time requirements; working with perception teams to combine reinforcement learning with vision, depth, and sensor data for robust decision-making; building and maintaining sim-to-real pipelines incorporating domain randomization and transfer learning techniques; conducting experiments on physical robots including designing safety protocols and monitoring for unexpected behaviors; utilizing simulation environments such as Isaac Gym, Gazebo, MuJoCo, and PyBullet for large-scale training before real-world validation; and continuously improving model efficiency to work within compute and latency limits on embedded robotic systems. Requirements include a Master's or PhD in Computer Science, Robotics, Machine Learning, or a 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 such as MuJoCo and Isaac Gym; a solid understanding of probability, statistics, and optimization; and experience training and deploying ML models in production systems. Benefits include daily free lunch, flexible PTO, comprehensive medical, dental, and vision coverage, 6 weeks fully paid parental leave plus an additional 6–8 weeks for birthing parents (12–14 weeks total), a 401(k) retirement plan through Empower, and generous employee referral bonuses. The company encourages unique thinking and is dedicated to creating a diverse and inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. If a reasonable accommodation is needed to participate in the application process or any part of the hiring process, applicants should contact the company, which is committed to providing equal access and will respond within 48 hours.

Senior Machine Learning Engineer - Reinforcement Learning

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