About the job
Motional, based in Pittsburgh, develops autonomous vehicles with a strong focus on safety, reliability, and accessibility. Supported by Hyundai Motor Group, Motional is committed to advancing physical AI and shaping the future of transportation. The company’s mission centers on making streets safer and encouraging sustainable mobility.
The Systems Readiness and Performance team connects software development with real-world deployment. This group handles system design, verifies and validates the autonomy stack, and sets as well as measures performance benchmarks. Team members work closely with autonomy, infrastructure, and operations partners to build the safety case for launching fully driverless IONIQ 5 robotaxis in Las Vegas.
Role overview
The Senior Engineer, Machine Learning Systems for Autonomy, joins the Autonomy Subsystems team to design and evaluate software modules that power autonomous vehicles. The role centers on assessing machine learning subsystems using offline model evaluations, open and closed-loop re-simulations, and on-road performance analysis. Defining and validating metrics that reflect subsystem performance is a key part of the job, along with sharing insights to help machine learning developers improve the models used in vehicles.
What you will do
- Design and evaluate machine learning software modules for autonomous vehicles
- Conduct offline assessments of models and analyze results from re-simulations
- Evaluate the on-road performance of machine learning models
- Define and validate metrics to measure autonomy subsystem performance
- Collaborate with machine learning developers to support improvements in deployed models
Requirements
- Experience as a systems engineer, with a background in safety-critical systems and machine learning model evaluation
- Interest in autonomy, robotics, and machine learning
- Prepared to help build production-ready systems for robotaxi deployment

