Robotics Simulation Intern at Bright Machines in San Francisco, CA

Summary: Bright Machines is an innovative company focused on transforming the manufacturing industry through intelligent automation. As a Robotics Simulation Intern, you will develop simulated robotic tasks and evaluate control policies for industrial automation applications, contributing to the creation of the factory of the future. Responsibilities: - Build and maintain simulation scenes in Isaac Lab for robot manipulation tasks, including cable routing, cable insertion, and pick-and-place - Implement, run, and analyze experiments to evaluate the effectiveness of different robotic policies in simulation - Support training workflows for robotic learning approaches, including hyperparameter tuning, fine-tuning, and performance benchmarking - Work closely with robotics and research engineers to investigate new task setups, validate approaches, and improve simulation fidelity and task success - Design, execute, and document experiments to measure performance, robustness, and failure modes - Analyze results and communicate findings through clear visualizations, summaries, and technical discussions Required Qualifications: - Pursuing a BS/MS in Robotics, Mechatronics, Mechanical Engineering, Electrical Engineering, Computer Science, Aerospace Engineering, or a related field - Experience with Isaac Lab, Isaac Sim, Omniverse, or similar robotic simulation tools - Experience with robotics, reinforcement learning, imitation learning, or control systems through coursework, research, or personal projects - Ability to interpret experimental data, analyze results, and communicate insights clearly - Strong problem-solving skills and attention to detail in experimental setup and evaluation - Examples of personal, academic, or professional projects that demonstrate hands-on robotics, simulation, or machine learning experience Preferred Qualifications: - Familiarity with robot manipulation, motion planning, or robot learning for contact-rich tasks - Experience training policies and tuning hyperparameters for reinforcement learning or other learning-based methods - Knowledge of robot kinematics, dynamics, control, and perception - Strong programming skills in Python - Experience working with robotic arms and manipulation tasks in either simulation or real hardware - Experience with experiment automation, logging, and visualization tools for ML or robotics workflows Required Skills: Isaac Lab, Robotics simulation, Reinforcement learning Important Skills: Python, Robot manipulation