Senior Motion Planning Engineer - Safety-Layer
Mission Summary:
The Safety-Layer Team is responsible for ensuring the Motional Autonomous Vehicle executes appropriate dynamic trajectories in both nominal and safety-critical scenarios. This team focuses on refining upstream motion plans to guarantee compliance with safety-driven requirements, executing highly dynamic evasive maneuvers at the AV’s physical limits, and implementing system-wide safety overrides. The team pursues these goals through a process of rigorous algorithmic design, implementation, validation, analysis in simulation, and comprehensive closed-course and public road evaluation.
As the team's responsibilities are growing to support more complex scenarios and the scaling of Motional’s deployment area, we are looking for a Senior Motion Planning - Safety-Layer to help build a robust motion planning safety-layer. You will work on enabling cutting-edge capabilities for Motional’s AV, including algorithm design and documentation, software development, metrics definition, simulation implementation and evaluation, and in-vehicle testing. As part of this role, you will maintain cross-functional relationships across the organization to help understand and communicate the impacts of their work on overall AV performance.
What you will work on:
Design, implement, and test algorithms for synthesizing trajectories and selecting trajectories across asynchronous generation sources to ensure AV behaviors adhere to safety-critical requirement specifications.
Develop evasive maneuver planning algorithms in conjunction with low-level control systems to safely use the full actuation capacity of Motional’s AV for collision avoidance.
Evaluate the role of multiple perception sensor modalities in refining the safety-layer’s identification of safety-critical scenarios.
Construct test/analysis tooling for isolated and system-level evaluation of safety-layer components and processes, select test parameters, and analyze test results.
Utilize, validate, and improve dynamic simulation environments to accelerate the design and analysis of safety-critical motion planning algorithms, including validating simulation models against real-world data.
Define and implement performance, comfort, and safety metrics for motion planning and safety systems, and perform quantitative analysis of fleet-wide vehicle data to validate design improvements and identify key areas of improvement.
Build a system-wide understanding of Motional’s autonomy stack components by supporting root-cause analysis of simulation, closed-course, and public road events from a motion planning and safety perspective.
Travel for in-person vehicle testing at Motional’s and our partner's deployment and test track locations, typically once every 4 to 6 months.
Desired Background:
MS, PhD preferred, in one of Control Theory / Robotics / Computer Science / Applied Math or a related field
3+ years of experience developing motion planning and collision avoidance related algorithms and components in an industrial setting, preferably the AV industry
Strong background in modern C++ programming (C++17, C++20), with an emphasis on developing high-performance and reliable systems
Experienced with concepts from motion planning including trajectory generation through numerical optimization and sampling-based approaches, cost and heuristic-based methods for trajectory selection, multi-modal prediction models, geometric and physics-based collision detection, time-series data processing, and data visualization
Familiarity with dynamic collision modeling, convex set processing, state machine logic, and multi-rate decision-making processes
Familiarity with agentic-based development tooling
Familiarity with Linux-based operating systems
Bonus Points:
General familiarity with machine learning, including supervised learning, reinforcement learning, training/test validation, etc.
Familiarity with vehicle dynamics modeling, including standard longitudinal/lateral vehicle dynamics models
Publications in Robotics/Controls or Autonomous Driving conferences/journals (IROS, ICRA, CoRL, RAL, TRO, CDC, ACC, TAC, CSL, Automatica, IV, ITSC, T-ITS)
Familiarity with SQL-based queries
Familiarity with Python
Familiarity with Gitlab, Bazel, VSCode / CLion
Familiarity with AV industry simulation tooling
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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