Senior Motion Planning Engineer – Trajectory Optimization

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.

We are seeking a Senior Software Engineer who is passionate about solving challenging autonomy problems and building production‑quality software for real‑world autonomous systems. This role is focused on motion planning, trajectory generation, and trajectory optimization for autonomous tractor‑trailer vehicles. You will contribute directly to the design, development, validation, and deployment of planning capabilities that enable safe and reliable autonomous driving.

• Design, develop, and optimize motion planning algorithms including trajectory generation, trajectory selection, behavior planning, and optimization‑based planning approaches for autonomous trucks.
• Develop planning solutions leveraging techniques such as graph search, sampling‑based planning, optimization‑based planning, spline/B‑spline trajectories, convex optimization, and Frenet‑frame approaches.
• Incorporate vehicle kinematic and dynamic constraints into planning systems to ensure safe, feasible, and comfortable vehicle behavior.
• Develop production‑quality software using modern C++ within a Linux environment while adhering to quality, safety, testing, and deployment best practices.
• Participate in software architecture discussions and contribute to technical designs that support scalable and maintainable autonomy systems.
• Develop and execute validation strategies across Software‑in‑the‑Loop (SiL), Hardware‑in‑the‑Loop (HiL), and Vehicle‑in‑the‑Loop (ViL) environments.
• Collaborate closely with Safety, Controls, Perception, Validation, and Simulation teams to develop safe and reliable autonomous driving behaviors.
• Investigate and debug vehicle behavior by reproducing issues in simulation, analyzing system performance, and implementing software improvements.
• Support vehicle integration, deployment activities, and post‑deployment investigations to ensure reliable autonomy performance.
• Participate in technical design reviews, code reviews, and continuous improvement initiatives across the Behaviors organization.
• Mentor junior engineers through collaboration, technical guidance, and knowledge sharing.

• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or a related technical field with 5+ years of industry experience; OR Master’s degree with 3+ years of experience; OR PhD with 1+ years of experience.
• Strong proficiency in modern C++ development within Linux‑based environments.
• Experience developing robotics, autonomous vehicle, ADAS, or other complex real‑time software systems.
• Strong experience developing motion planning, trajectory generation, trajectory optimization, behavior planning, or decision‑making systems for robotics or autonomous systems.
• Solid understanding of vehicle dynamics, vehicle kinematics, trajectory feasibility, and planning system architecture.
• Strong foundation in linear algebra, numerical optimization, geometry, and robotics algorithms.
• Strong understanding of software engineering fundamentals, system design principles, and scalable development practices.
• Experience working across the full software development lifecycle, from design and implementation through validation, deployment, and operational support.
• Strong problem‑solving skills and the ability to debug complex system‑level issues.
• Excellent communication and collaboration skills within cross‑functional engineering teams.
• Ability to work independently while contributing effectively within a highly collaborative environment.

• Experience with motion planning, trajectory optimization, behavior prediction, or decision‑making systems for autonomous vehicles.
• Experience with Model Predictive Control (MPC), convex optimization, quadratic programming (QP), nonlinear optimization,…