Machine Learning Engineer II - Learned Planning (Reinforcement Learning) at Torc Robotics

Department: AutonomyEducation: education_optional

Compensation

$153,200 – $183,800/yr

Setup: Remote
Location: Ann Arbor, Michigan
Type: Full-time
Level: mid
Posted: Sep 29, 2026

Description

Torc is hiring a Machine Learning Engineer II – Learned Behaviors to develop, train, validate, and deploy machine learning models for learned behavior systems in autonomous trucking. The role focuses on behavior cloning, imitation learning, reinforcement learning, model pipelines, data workflows, simulation and fleet-log testing, and infrastructure for experimentation and reproducibility. Candidates need a relevant bachelor’s degree with 4+ years of industry experience or a master’s degree with 2+ years of experience, along with Python, PyTorch, large-scale model training, and autonomy-systems knowledge. The position is available in Ann Arbor, Michigan, in a hybrid capacity, or remotely in the United States, with a US pay range of $153,200 to $183,800.

Required Skills

Python
PyTorch
Imitation learning
Reinforcement learning
Sequence modeling
Transformers
Graph neural networks
Model training pipelines
Large-scale datasets

Additional Information

Minimum Education: Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field
Required Previous Experiences: 4+ years of industry experience
Experience applying imitation learning, reinforcement learning, or sequence modeling to robotics, autonomous systems, or complex control environments
Experience writing production-quality machine learning code in Python and PyTorch
Experience training and evaluating machine learning models with large datasets and scalable compute environments
Experience debugging model behavior, analyzing performance metrics, and iterating on training pipelines
Experience collaborating with cross-functional teams to integrate machine learning models into larger software systems
Preferred Qualifications: Experience in autonomous driving, robotics, or simulation-based training environments
Experience with reinforcement learning frameworks or distributed training systems such as Ray
Experience with simulation environments or large-scale behavior datasets
Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems
Experience deploying machine learning models into production or real-world robotics systems
Translation Company Name: Torc Robotics