Lead the research and development of novel algorithms and sub-systems for motion planning in autonomous driving, expanding the Operational Design Domain.
Lead cross-functional projects to define new or upgrade existing interfaces to solve problems.
Monitor overall system performance to identify areas for improvement and develop technical strategies to address deficiencies.
Guide cross-functional project teams to provide comprehensive solutions and demonstrate the ability to think beyond the confines of the planning system.
Architect and integrate complex combinations of motion planning and prediction algorithms, driving their evaluation and refinement for real-world deployment.
Design and build a robust, scalable, and high-performance codebase that facilitates rapid exploration, prototyping, and rigorous evaluation of innovative motion planning approaches and algorithms.
Drive technical collaboration and interface seamlessly with perception and prediction components upstream and trajectory optimization, tracking and control components downstream, ensuring end-to-end system performance.
Leverage deep software development and research expertise to teach others better software practices and principles, fostering a culture of technical excellence.
Guide and mentor junior and senior team members, cultivating a culture of product-focused engineering, rigorous research, and advanced development.
Requirements
PhD preferred in Robotics, Computer Science, Computer Engineering, Mechanical Engineering, or a related field; or a Master's degree with 7+ years of experience in the robotics (preferably AV industry).
10+ 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.
Past experience owning and leading technical development on complex features from problem formulation through research, implementation, and deployment in a production environment, demonstrating significant impact.
Thirst for knowledge, continuous innovation, and a drive to push the boundaries of autonomous driving technology, acting as a technical thought leader.
Preferred: Experience with probabilistic models, including but not limited to Gaussian mixture models, Hidden Markov Models, and Particle Filters.
Preferred: Experience with machine learning techniques (such as Bayesian modeling and inference techniques) for decision making under uncertainty.
Preferred: Experience with the Bazel build framework.
Benefits
medical
dental
vision
401k with a company match
health saving accounts
life insurance
pet insurance
Additional forms of compensation such as a bonus or company equity
Candidates for certain positions are eligible to participate in Motional’s benefits program
ATS Keywords
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