Principal Engineer Motion Planning

Description

Motional is seeking a technical expert for its Planning team to define motion planning and control systems for secure, effective, and comfortable fleet operation in complex environments. This role requires expertise in cutting-edge research, advanced algorithm development, and robust software building to generate safe, comfortable, and intuitive routes and motions. The position focuses on contributing to production-ready autonomous vehicles through innovative and scalable planning solutions.

Role Responsibilities

• Lead the research and development of novel algorithms and sub-systems for motion planning in autonomous driving, expanding the Operational Design Domain, including advanced search-based and geometry-based methods and probabilistic decision-making under uncertainty.
• Lead cross-functional projects to define new or upgrade existing interfaces to solve problems.
• Monitor overall system performance, identify improvement areas, and develop technical strategies to address deficiencies.
• Guide cross-functional teams to deliver comprehensive solutions beyond the planning system scope.
• Architect and integrate complex combinations of motion planning and prediction algorithms for real-world deployment.
• Design and build a robust, scalable, high-performance codebase enabling rapid prototyping and rigorous evaluation.
• Collaborate with perception and prediction components upstream and trajectory optimization, tracking, and control components downstream to ensure end-to-end system performance.
• Promote strong software engineering practices and mentor junior and senior engineers.

Requirements

• PhD preferred in Robotics, Computer Science, Computer Engineering, Mechanical Engineering, or related field; or Master’s degree with 7+ years of robotics experience.
• 10+ years of research experience in robotics or motion planning with a track record of state-of-the-art contributions.
• 5+ years of C++ software development focused on high-performance and reliable systems.
• Experience leading complex features from problem formulation through deployment in production environments.

Preferred Skills

• Experience with probabilistic models such as Gaussian Mixture Models, Hidden Markov Models, and Particle Filters.
• Experience with machine learning techniques including Bayesian modeling and inference for decision-making under uncertainty.
• Experience with Bazel build framework.

Compensation and Benefits

• Salary range: $240,000–$330,000 USD (base salary).
• Eligibility for additional compensation such as bonus or company equity.
• Benefits may include medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more.