Senior Engineer, Autonomy ML Systems

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. They are seeking a talented senior engineer to contribute to the evaluation of machine learning subsystems, focusing on designing and evaluating modules of the autonomy software.

Responsibilities:

• Define, prototype, and validate advanced metrics that bring new insights to model performance evaluation for autonomy subsystems (mainly focused on perception, prediction, and planning)
• Assess coverage of existing training and testing, then curate test sets that sufficiently capture Motional’s intended deployment operational design domain, across many axes (agent types, interaction types, map/spatial, etc.)
• Evaluate machine learning model performance against these metrics and tests
• Assess system-level performance and subsystem contribution to system behavior through large-scale data analysis of on-road and simulation events
• Define performance requirements for autonomy subsystems, and supporting analyses required to establish these targets
• Coordinate subsystem-level evaluation with other system-level testing efforts across the systems team in support of the safety case and safety claims

Requirements:

• An engineer who has demonstrated strong cross-functional collaborative skills and is highly self-starting. This is a highly cooperative role across systems, autonomy, infrastructure, and other parts of the organization
• Proven engineer with 5+ years of experience working on high-tech safety critical systems or robotics, ideally from a systems, robotics, or similar background
• Master's degree in relevant fields (systems, robotics, ML, CS, etc.) or Bachelor's degree plus significant relevant in-field experience
• Skilled Python developer, familiarity with analyzing the large scale data required to train and test ML models
• Experience designing unique metrics that capture key aspects of system behavior and are used to enhance model development
• Experience training machine learning models, familiarity with state-of-the-art ML model architectures
• Deep experience with a specific aspect of machine learning for autonomous robotics (perception, prediction, or planning)
• Knowledge of C++, especially applied to safety critical systems
• Experience with systems verification and validation techniques
• Experience with regression testing updates to already-deployed software in a safety-critical environment
• Experience with automotive standards (E.g: ISO 12207, ISO 26262, ISO 21448)
• Experience with software quality management and assurance activities (E.g: IATF 16949, ISO 9001)
• Thorough understanding of robotics systems including sensors, actuators, mechatronics and software systems
• Work in cross collaboration teams to address problems and find solutions