Role responsibilities:- Lead the research and development of novel algorithms for motion planning in autonomous driving, including but not limited to advanced search-based methods, sophisticated geometry-based methods, and decision making under uncertainty with a strong emphasis on probabilistic approaches.
- 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 your deep software development and research expertise to teach others better software practices and principles, fostering a culture of technical excellence.
- Guide and mentor junior team members, cultivating a culture of product-focused engineering, rigorous research, and advanced development.
What we're looking for:- PhD preferred in Robotics, Computer Science, Computer Engineering, Mechanical Engineering, or a related field; or a Master's degree with 2+ years of experience in the robotics (preferably AV industry)
- 5+ years of research experience in robotics / motion planning, with a proven track record of contributing to state-of-the-art solutions
- 3+ 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.
- Thirst for knowledge, continuous innovation, and a drive to push the boundaries of autonomous driving technology.
Bonus points(not required):- Experience with probabilistic models, including but not limited to Gaussian mixture models, Hidden Markov Models, and Particle Filters.
- Experience with Bayesian modeling and inference techniques for decision making under uncertainty.
- Experience with the Bazel build framework
We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.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.
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.
Salary Range
$172,000-$229,000 USD
