Senior Manager, Engineering - Learned Vehicle Intent (Hands-On)

Torc Robotics • Ann Arbor, MI

10d • Hybrid

About The Position

At Torc, we are building a fully learned behavior stack. You will lead multiple teams responsible for developing and scaling learned behavior models that drive decision-making in Torc’s autonomous trucking system. These teams sit at the intersection of reinforcement learning, imitation learning, and multi-agent systems, shaping how our vehicles behave in complex, real-world environments — from highway merging to dense traffic interactions. You will be responsible for both technical direction and organizational leadership, ensuring your teams deliver production-ready behavior models that are safe, robust, and scalable. This is a hands-on technical leadership role — the expectation is Staff-level technical depth combined with the ability to lead, grow, and align multiple engineering teams.

Requirements

• 10+ years of experience in applied machine learning, autonomy, robotics, or related domains
• Proven experience operating at a Staff or higher technical level, with deep expertise in: Reinforcement learning, Imitation learning / behavior cloning, Multi-agent systems
• 5+ years of experience leading engineering teams, ideally across multiple teams or domains
• Demonstrated success defining and delivering technical roadmaps for complex ML systems
• Strong programming background in Python and modern ML frameworks (e.g., PyTorch, PufferDrive)
• Deep understanding of ML architectures and training systems, including scaling, data pipelines, and deployment
• Experience integrating ML models into production systems, ideally within autonomy or robotics stacks
• Strong cross-functional collaboration skills and ability to influence across teams

Nice To Haves

• Experience in autonomous vehicles, trucking, or large-scale robotics systems
• Experience deploying RL or learned behavior models in production environments
• Familiarity with simulation environments, scenario generation, and validation frameworks
• Experience with Ray or distributed training infrastructure
• Background in system-level integration of ML models into planning or control systems
• PhD in Computer Science, Artificial Intelligence, or related field with a track record in learned behaviors or reinforcement learning

Responsibilities

• Own the technical vision and roadmap for Learned Vehicle Intent (LVI), aligning model development with product and safety goals
• Lead and scale 2–3 teams of ML engineers, driving execution across model development, training, and deployment
• Set and uphold a high bar for technical excellence in reinforcement learning, imitation learning, and behavior modeling
• Guide architecture decisions for policy learning systems, including behavior cloning, RL, and multi-agent interaction models
• Drive development of scalable training pipelines, data infrastructure, and experimentation frameworks
• Partner cross-functionally with perception, prediction, analytical planning, simulation, and safety teams to integrate learned behaviors into the autonomy stack
• Ensure robust validation and evaluation of behavior models, including failure analysis and performance tracking across simulation and real-world environments
• Establish best practices for data strategy, model iteration, and system-level integration
• Mentor senior and staff engineers, fostering growth, ownership, and technical leadership within the team
• Lead team planning, execution, and delivery, ensuring alignment with broader organizational priorities
• Build, develop, and retain high-performing engineering teams
• Drive hiring, onboarding, and organizational design across LVI teams
• Provide coaching, career development, and performance management
• Establish clear goals, metrics, and accountability frameworks
• Manage team capacity, prioritization, and execution against roadmap
• Communicate progress, risks, and strategy to senior leadership
• Operate effectively in a fast-paced, ambiguous environment with evolving technical and product requirements

Benefits

• A competitive compensation package that includes a bonus component and stock options
• 100% paid medical, dental, and vision premiums for full-time employees
• 401K plan with a 6% employer match
• Flexibility in schedule and generous paid vacation (available immediately after start date)
• Company-wide holiday office closures
• AD+D and Life Insurance
• Sign-on payments
• Relocation
• Other forms of compensation may be provided as part of a total compensation package

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree
• Number of Employees: 251-500 employees