Principal Engineer Team Lead - Trajectory Planning Lead

Mission Summary

As a Technical Lead Manager at Motional, you'll lead a team responsible for the development and delivery of core trajectory planning algorithms via numerical optimization for autonomous vehicles. In this role, you will be at the forefront of shaping the motion planning and control systems that enable our fleet to navigate complex environments safely, efficiently, and comfortably. As a key leader, you will drive the development and continuous performance improvements of cutting‑edge trajectory generation algorithms, collaborate with cross‑functional teams (Planning, Perception, Prediction, Localization, ML Products, and Systems Engineering), and mentor a talented group of highly skilled engineers to deliver state‑of‑the‑art solutions.

If you are passionate about autonomous driving and being part of our commercial launch this year, thrive on solving challenging real‑world problems, and eager to make a significant impact in a rapidly evolving field, we want to hear from you!

• Lead and scale a high‑impact trajectory planning team, defining its technical vision, execution strategy, and long‑term organizational role within the Motion organization.
• Drive commercial launch readiness for trajectory planning by delivering on‑road driving behavior improvements (safety, comfort, and assertiveness) across the fleet through feature expansion, continuous performance improvements, and innovation through state‑of‑the‑art methods.
• Apply a rigorous, metrics‑driven framework to quantify and improve on‑road performance. Champion leveraging existing training and evaluation pipelines to ensure scalable, production‑ready delivery.
• Manage the computational efficiency and real‑time performance of trajectory generation algorithms, ensuring latency budget compliance.
• Lead the rapid triage and root‑cause analysis (RCA) of critical fleet incidents, translating real‑world edge cases into immediate algorithmic refinements and validation sets.
• Oversee the successful execution of complex, multi‑team initiatives, ensuring technical alignment from design through deployment while maintaining a rigorous standard for testing and validation to meet the high safety bars required for our commercial launch.
• Coordinate with peer leads to provide technical leadership, making consequential decisions on architectural direction, strategic investments, tactical execution, and technical debt reduction. Ensure technical excellence through rigorous design and code reviews while actively facilitating the professional growth and mentorship of your engineering team. Set and drive ambitious goals that challenge the team to deliver industry‑leading trajectory planning solutions.
• Define and negotiate quarterly and annual technical roadmaps aligned with company‑level autonomy milestones in coordination with project managers and execute plans on schedule.

• Proven Engineering Leadership: 2+ years of experience managing high‑performing development teams, with a demonstrable track record of inspiring, mentoring, and coaching engineers and driving measurable productivity gains.
• Ship‑to‑Production Mindset:
  Experience leading the delivery of production‑quality algorithms in a high‑stakes environment (Autonomous Vehicles, Robotics, or Aerospace). You know what it takes to move from a prototype to a commercially viable product.
• Strategic Vision:
  Ability to look beyond the immediate deliverables to define and defend a balanced technical roadmap that balances long‑term architectural health with the urgent needs of a 2026 commercial launch.
• Technical Domain Expertise:
  Deep theoretical and practical expertise in numerical optimization and optimal control. You should be highly proficient in areas such as Model Predictive Control, nonlinear programming, and convex optimization applied to real‑time trajectory generation.
• Advanced Motion Planning:
  Significant experience solving motion planning problems under uncertainty, including interaction‑aware planning with dynamic agents and complex environmental constraints. Experience with Machine Learning based approaches is a significant plus.
• Full‑Stack Robotics Context:
  Strong…