Solve trillion dollar opportunity in industry hurting from lack of skilled labor at Path Robotics
Requirements
- Master’s or PhD in Computer Science, Robotics, Machine Learning, or related field, or equivalent practical experience.
- Strong knowledge of reinforcement learning algorithms and theory.
- 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.
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.
Other
- Master’s or PhD in Computer Science, Robotics, Machine Learning, or related field, or equivalent practical experience.
- Flexible PTO
- Medical, Dental and Vision insurance with 100% coverage on monthly medical premiums for you and any dependents on select plans
