Principal Engineer Trajectory Generation

About the Role

We are seeking a highly experienced and visionary Principal Engineer to join our Motion Planning & Control team. In this pivotal role, you will be a technical thought leader, driving the research, design, development, and deployment of cutting-edge algorithms for Motional’s autonomous vehicles. You will work on trajectory generation, sophisticated control systems, and robust collision avoidance techniques. You will be instrumental in expanding our Operational Design Domain (ODD) and ensuring our vehicles operate safely, comfortably, and intuitively in complex real-world environments.

This is a unique opportunity to shape the future of autonomous driving, translating groundbreaking research into production-ready software that directly impacts the safety and performance of our self-driving fleet.

Role Responsibilities

• Develop state-of-the-art trajectory generation and motion control algorithms to ensure safe and comfortable vehicle motion
• Design and build robust and scalable software that enables real on-road impact by evaluating different control techniques and motion planning algorithms
• Push boundaries of existing proven trajectory generation methods to enable data-driven approaches
• Leverage modern development toolchains including testing, simulation, and continuous integration, to enable rapid development cycles
• Provides high-quality code and design reviews based on a deep understanding of the teams’ services and technologies
• Collaborate closely with perception, prediction, planning, and control teams to seamlessly integrate our trajectory generation algorithms and drive the holistic development of our autonomous driving system.

Experience to Bring

• Masters or PhD in Robotics, Electrical Engineering, Computer Engineering, Computer Science, Mechanical Engineering, or a related field.
• 7+ years of research experience in robotics / motion planning, with a proven track record of contributing to state-of-the-art solutions and leading significant projects.
• 5+ years of C++ software development, with an emphasis on developing high-performance and reliable systems.
• Proven track record of delivering production-quality algorithms for autonomous trajectory generation/control in a leading role.
• Expertise in optimal control and numerical optimization.
• Theoretical knowledge and engineering experience in motion planning under uncertainty, and interaction with dynamic agents and environment.
• Familiarity with robotics algorithms in localization, perception, motion planning, and controls for autonomous systems.
• Strong communication, interpersonal, and management skills.

Bonus Points

• Proven track record of publications in relevant conferences
• In-depth understanding of common Machine Learning and Deep Learning algorithms
• Python development experience
• Experience with the Bazel build system

Salary Range

$212,000 - $283,975 USD

The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.

Benefits

Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

About Motional

Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more. Our journey is always people first. We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and m