Senior Motion Planning and Control Engineer

Summary

Join Motional as a Senior Motion Planning and Controls Engineer to contribute to the development of robust motion planning and control pipelines for autonomous vehicles. You will design, implement, and test low-level controllers, integrate trajectory generation and motion tracking, develop testing and analysis tools, and architect dynamic simulation environments. Responsibilities include defining performance metrics, analyzing vehicle data, and implementing optimization frameworks. The role requires collaboration with cross-functional teams and occasional travel for vehicle testing. This position offers a competitive salary and benefits package.

Requirements

• MS, PhD preferred, in one of Control Theory / Robotics / Computer Science / Applied Math or a related field
• 3+ years of experience developing controls / motion planning related algorithms and components in an industrial setting
• Experienced with concepts from control theory, including linear/nonlinear systems, state estimation / Kalman filtering, model predictive control, data-driven system identification, time-series data processing, and data visualization
• Familiarity with numerical optimization, quadratic/conic programming, convex optimization, nonlinear programming, and non-convex optimization
• Familiarity with Python and C++/C
• Familiarity with Linux-based operating systems

Responsibilities

• Design, implement, and test low-level controllers, state estimators, and state-machine logic that directly interface with platform sensors and actuators to produce performant, comfortable, and safe motion tracking
• Integrate upstream trajectory generation and downstream motion tracking controllers through principled trajectory interface design, including generator / controller state machine logic design and trajectory communication formulation
• Develop test/analysis tooling for isolated evaluation of motion tracking performance and incremental integration testing that incorporates upstream components (trajectory generation, planning, perception, etc.), select test parameters, and analyze test results
• Architect and implement dynamic simulation environments that accelerate the design and analysis of motion planning and control algorithms, including validation of simulation models against real-world data
• Define and implement performance, comfort, and safety metrics for motion planning and control, and perform quantitative analysis of fleet-wide vehicle data to validate design improvements and identify key areas of improvement
• Formulate, implement, analyze, and test optimization and machine learning-based frameworks for dynamic trajectory synthesis
• 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 control 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

Preferred Qualifications

• Familiarity with vehicle dynamics and modeling, including longitudinal/lateral vehicle dynamics, tire modeling, EV drive-train / steer dynamics, etc
• General familiarity with machine learning, including supervised learning, reinforcement learning, training/test validation, etc
• Publications in Controls/Robotics or Autonomous Driving conferences/journals (CDC, ACC, TAC, CSL, Automatica, IROS, ICRA, CoRL, RAL, TRO, IV, ITSC, T-ITS)
• Familiarity with SQL, Looker, MATLAB/SimuLink
• Familiarity with Gitlab, Bazel, VSCode / CLion
• Familiarity with AV industry simulation tooling
• Familiarity with CAN communication protocol, AUTOSAR, AURIX
• Familiarity with real-time kinematic (RTK) GPS localization

Benefits

• Medical
• Dental
• Vision
• 401k with a company match
• Health saving accounts
• Life insurance
• Pet insurance