Senior Machine Learning Engineer II, AV Performance Analytics

We're Cruise, a self-driving service designed for the cities we love.

We’re building the world’s most advanced self-driving vehicles to safely connect people to the places, things, and experiences they care about. We believe self-driving vehicles will help save lives, reshape cities, give back time in transit, and restore freedom of movement for many.

In our cars, you’re free to be yourself. It’s the same here at Cruise. We’re creating a culture that values the experiences and contributions of all of the unique individuals who collectively make up Cruise, so that every employee can do their best work. 

Cruise is committed to building a diverse, equitable, and inclusive environment, both in our workplace and in our products. If you are looking to play a part in making a positive impact in the world by advancing the revolutionary work of self-driving cars, come join us. Even if you might not meet every requirement, we strongly encourage you to apply. You might just be the right candidate for us.

The Autonomous Vehicle (AV) software stack is a sophisticated workload that includes compute and data intensive functions within perception, prediction, planning and control. Maturity of the software not only depends on feature development but also meticulous and well defined analysis to provide feedback to feature engineering and testing teams. The Performance analytics is such a team bridging feature optimization and various testing platforms. Closely collaborating with Data science and Autonomy teams, we discover and define performance metrics enabling trend & insights for performance and reliability; we develop quantitative analysis and applications to facilitate development; and we continuously monitor on-road and testing status and derive release projection, feeding to leadership decisions.

In this role, you’ll closely work with Data scientists, System Engineering and Autonomy teams to build up infrastructures to speed up various feature minings & learnings, build ML models to evaluate simulation performance across multiple platforms and continuously improve models for usability, scalability and adoption. You will have the opportunity of influencing how the test and data platform is designed, built and evaluated, work with product/project management defining the roadmap.

• Work on feature development for autonomous vehicle reliability dataset.

• Collaborate with autonomy engineers to improve the quality and composition of our dataset.

• Build machine learning models to scale up faulty segment and test cases management

• Build end-to-end ML workflow, with usability, scalability adoption …