Jobs in Ann Arbor, MI

About the role

As a Senior Machine Learning Engineer – Learned Planner / Reinforcement Learning, you will develop and deploy machine learning models that drive decision-making for autonomous trucks. This role focuses on owning model development and delivery for scoped problem areas, contributing to architecture decisions, and driving improvements in model performance, reliability, and iteration speed within the autonomy stack.

What you'll bring

• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or related technical field with 6+ years of industry experience, OR Master’s degree with 3+ years OR PhD with 1+ years of experience
• Experience applying reinforcement learning, imitation learning, or sequence modeling to robotics, autonomous systems, or complex control problems
• Strong programming skills in Python and PyTorch, with experience writing production-quality ML code
• Experience training, evaluating, and improving models using large-scale datasets and distributed compute environments
• Solid understanding of ML architectures used in autonomy systems (e.g., transformers, RNNs, graph neural networks, policy networks)
• Experience debugging model behavior, analyzing performance metrics, and improving model reliability
• Ability to translate ambiguous problems into structured ML solutions and deliver results independently
• Experience collaborating cross-functionally to integrate ML models into larger autonomy systems
• Experience in autonomous driving, robotics, or simulation-based training environments
• Experience with reinforcement learning frameworks or distributed training systems (e.g., Ray)
• Experience working with simulation environments, scenario generation, or large-scale behavior datasets
• Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems

Benefits