Senior Motion Planning Engineer

Role overview

This is a senior research and engineering role on a motion planning team building production-ready planning software for autonomous vehicles. The position involves cutting-edge algorithm research combined with shipping robust, high-performance code that generates safe, comfortable, and intuitive routes and motions. It is a hybrid or fully remote opportunity based in Boston, Pittsburgh, or Las Vegas.

Responsibilities

- Lead research and development of novel motion planning algorithms, including advanced search-based methods, geometry-based methods, and probabilistic decision making under uncertainty - Architect and integrate combinations of motion planning and prediction algorithms and drive their evaluation and refinement for real-world deployment - Design and build a scalable, high-performance codebase that supports rapid exploration, prototyping, and rigorous evaluation of new approaches - Collaborate closely with upstream perception and prediction components and downstream trajectory optimization, tracking, and control to ensure end-to-end performance - Teach and promote strong software practices and principles across the team - Guide and mentor junior engineers and cultivate a culture of product-focused engineering and rigorous research

Requirements

- PhD preferred in Robotics, Computer Science, Computer Engineering, Mechanical Engineering, or a related field, or a Master's degree with 2+ years of robotics experience, preferably in the autonomous vehicle industry - 5+ years of research experience in robotics or motion planning with a track record of contributing to state-of-the-art solutions - 3+ years of C++ development focused on high-performance, reliable systems - Experience owning and leading complex features from problem formulation through research, implementation, and production deployment - Continuous learning mindset and drive to push the boundaries of autonomous driving technology

Nice to have

- Experience with probabilistic models such as 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

Benefits and work setup

- Base salary range of $172,000 to $229,000 USD, with potential bonus or equity participation - Hybrid schedule with in-office time in Boston, Pittsburgh, or Las Vegas, or fully remote - Benefits program includes medical, dental, vision, 401k with company match, health savings accounts, life insurance, and pet insurance