Architect and implement metrics and analyses to introspect autonomous driving software performance at subsystem interfaces across the autonomy stack; work closely with autonomy developers and system engineers.
Propose and develop new statistical and ML methods to quantify performance and identify patterns of system and subsystem behavior across diverse scenes and operational domains.
Develop and apply methods to introspect the operation of ML components in the autonomy stack.
Create informative, interactive results and dashboards that provide rapid insight for development and verification, and are routinely used by partner teams.

5+ years applied experience with robotics or autonomous systems software, from sensors and perception through planning and control of the vehicle.
3+ years evaluating dynamic systems using numerical and ML approaches, including time series data, state derivatives, dynamics, and interconnected subsystems.
Proficiency developing Python in production team environments.
Comfort working with C++ codebases, including reading and instrumenting core algorithms.
Demonstrated technical leadership, including driving decisions and influencing architecture.
PhD, Master’s, or Bachelor’s degree in Computer Science, Robotics, Mechanical or Aerospace Engineering, Machine Learning, or a related field.

Senior Software Engineer, Autonomy Evaluation

Key skills