Motional is seeking a Senior Engineer for their Autonomy ML Systems team to evaluate and enhance machine learning subsystems as part of their mission to deploy driverless vehicles. The ideal candidate will have experience in safety-critical systems, strong collaboration skills, and proficiency in Python, with a focus on autonomous vehicle technology
Job Summary
The team is responsible for verifying and validating the autonomy stack to build a definitive safety case for commercial robotaxi launch.
This role involves defining advanced metrics to evaluate model performance across perception, prediction, and planning subsystems.
Candidates must be skilled Python developers capable of analyzing large-scale data required to train and test machine learning models.
Matching Summary
Match Score: 85
Motional is seeking a Senior Engineer for their Autonomy ML Systems team to evaluate and enhance machine learning subsystems as part of their mission to deploy driverless vehicles. The ideal candidate will have experience in safety-critical systems, strong collaboration skills, and proficiency in Python, with a focus on autonomous vehicle technology.
Salary
Base: $125,000 - $167,000 USD; Bonus/Equity: Additional forms of compensation may include bonus or company equity; Benefits: Medical, dental, vision, 401k match, health saving accounts, life insurance, pet insurance
Skills & Requirements
Must-have
5+ years experience in safety critical systems
Python development for large scale data analysis
Experience designing unique performance metrics
Cross-functional collaboration skills
Evaluation of ML models for autonomy
Nice-to-have
Experience training machine learning models
Knowledge of C++ applied to safety critical systems
Familiarity with ISO automotive standards
Deep expertise in perception or planning
Experience with regression testing in safety environments
Key Requirements
Master's degree or Bachelor's with significant experience
5+ years working on high-tech safety critical systems
Proven engineer with robotics or systems background