About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team
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.
What You’ll Do
- 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
Leadership Responsibilities
- 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
What You’ll Need to Succeed
- 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
Bonus Points
- 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
Work Location: For this position, we are open to hiring in either the Ann Arbor, MI OR Blacksburg, VA (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States
Perks of Being a Full-time Torc’r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
- 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
At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.
Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: 102683
Hiring Range for Job Opening US Pay Range
$195,500—$234,600 USD
