Torc Robotics - Senior Motion Planning Engineer - Trajectory Optimization
Requirements
• 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, 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. • Work Location: For this position, we are open to hiring in Ann Arbor, MI, Blacksburg, VA, Fort Worth, TX office work locations in a hybrid capacity. We are also open to hiring Remote in the United States & Canada • Work Location:
Responsibilities
• 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.
Benefits
• 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 matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures • AD+D and Life Insurance • 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: 102795 • Hiring Range for Job Opening • $160,800—$193,000 USD
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