Senior Controls Engineer - Autonomy
- Bringup of a reverse driving controller (longitudinal and lateral) from scratch to support reverse driving capabilities across Motional’s fleet of AVs.
- 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.
- 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.
- 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.
- 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.
- 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
- 3+ years of industry experience implementing C++/C and Python
- Familiarity with Linux-based operating systems
- Proven experience in an industry setting with the implementation of reverse driving trajectory tracking control for vehicles
- 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
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