Torc Robotics
Machine Learning Engineer II - Learned Planning (Reinforcement Learning)
$153K–$184K
Remote - US, Ann Arbor, MI +1 · Remote · Full-time · Posted Sep 29, 2026
- Location
- Remote - US, Ann Arbor, MI
Ann Arbor, Michigan, United States - Experience
- 4+ years with a Bachelor’s degree, or 2+ years with a Master’s degree.
- Education
- Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field; alternatively, a Master’s degree.
About the job
Develop, validate, and integrate learned behavior models that support decision-making for autonomous trucks.
What you'll do
- Train and improve behavior models using behavior cloning, imitation learning, and reinforcement learning; analyze performance and failure modes.
- Build production-quality ML code, training pipelines, data workflows, and experimentation tools.
- Collaborate with autonomy, simulation, validation, and engineering teams to integrate and evaluate models across driving environments.
What they ask for
- Bachelor’s degree in a related technical field with 4+ years of industry experience, or a Master’s degree with 2+ years of experience.
- Experience applying machine learning to robotics, autonomous systems, or complex control environments.
- Strong Python and PyTorch programming skills, including production-quality ML code.
- Experience training and evaluating models with large datasets and scalable compute environments.
Nice to have
- Experience in autonomous driving, robotics, or simulation-based training.
- Experience with reinforcement learning frameworks or distributed training systems such as Ray.
Pay
$153,200 — $183,800 USD (base salary)
Tools
Python, PyTorch, Ray, transformers, graph neural networks
AI focus
Develop and deploy learned behavior models for autonomous truck decision-making, including imitation learning, reinforcement learning, and sequence modeling.
Model-written summary · the original posting is authoritative