Machine Learning Engineer II

Collaborating closely with perception, prediction, planning, and safety teams, the full-time Machine Learning Engineer II will develop and deploy behavior models that enhance decision-making for autonomous trucks, while working remotely or from the office in Montreal or Ann Arbor. Key responsibilities Develop and train machine learning models for acquired behavior systems using techniques like behavior cloning, imitation learning, and reinforcement learning Implement production-quality AI code to support training, evaluation, and inference of models within the autonomy stack Analyze model performance, identify failure modes, and propose improvements to enhance robustness across various scenarios Required qualifications Bachelor's degree in computer science, robotics, electrical engineering, machine learning, or a related technical field with at least 4 years of experience, or a master's degree with at least 2 years of experience Experience applying machine learning techniques such as imitation learning, reinforcement learning, or sequence modeling in autonomous systems or complex control environments Strong programming skills in Python and PyTorch, with experience in writing production-quality AI code Experience training and evaluating machine learning models using large datasets and adaptive computing environments Understanding of AI architectures used in autonomous driving systems, such as transformers, graphical neural networks, or sequence models