Senior Motion Planning Engineer – Trajectory Optimization

Meet the Team

Join Torc's Behaviors Team, where we develop the planning, prediction, and decision-making systems that determine how our autonomous trucks navigate the world safely, efficiently, and predictably. Our team operates at the intersection of robotics, machine learning, optimization, simulation, and safety, building the core autonomy capabilities that translate perception into action.

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. You will work closely with engineers across autonomy, controls, simulation, safety, and validation to help deliver robust autonomy behaviors at scale.

What You'll Do

• 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.

What You'll Need to Succeed

• 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.

Bonus Points!

• 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, or other optimization-based planning techniques.
• Experience applying machine learning techniques such as imitation learning, reinforcement learning, or hybrid planning architectures.
• Understanding of vehicle dynamics, controls, state estimation, and trajectory tracking.
• Experience developing software in both C++ and Python environments.
• Experience integrating machine learning models into real-time or production systems.
• Experience working with simulation platforms and large-scale autonomy validation environments.
• Experience with robotics frameworks such as ROS/ROS2, Autoware, Apollo, or similar autonomy platforms.
• Exposure to CUDA, GPU acceleration, TensorRT, or high-performance compute environments.
• Experience supporting on-vehicle testing, debugging, and deployment activities.
• Passion for autonomous vehicles, robotics, and solving complex real-world engineering challenges.