Machine Learning Engineer - Robot Manipulation

Qualifications

• Must-have:
• MS or PhD in machine learning, computer science, robotics, or a related field.
• Strong practical experience in training and deploying machine learning models for real-world applications.
• Deep understanding of reinforcement learning (RL) and imitation learning (IL) and their application to robotics.
• Proficiency in programming languages and tools commonly used in machine learning (e.g., Python, PyTorch).
• Experience with data collection, preprocessing, and management in the context of training ML models.
• Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
• Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.
• Nice-to-have:
• Familiarity with robotic simulation environments (e.g., Gazebo, MuJoCo) and experience in sim-to-real transfer.
• Experience in:
• Designing and implementing reward functions for complex manipulation tasks.
• Developing models that can handle noisy, incomplete, or sparse data.
• Deployment of ML models to edge devices for real-time inference.
• Accelerating ML training processes using GPU, TPU, or other HW accelerators.
• Using reinforcement learning frameworks, e.g. Stable Baselines, RLlib, or similar.
• General knowledge of robotics principles, including kinematics, dynamics, and control.
• Publications or contributions to the machine learning community, particularly in areas related to robotics or reinforcement learning.