We're the driverless car company. We’re building the world’s best autonomous vehicles to safely connect people to the places, things, and experiences they care about.
Our vehicles are on the road in California, Arizona, and Michigan navigating some of the most challenging and unpredictable driving environments. We’re hiring people who want to solve some of today’s most complex engineering challenges and make a positive impact.
In this role, you will analyze petabytes of time-series data to both describe the whole-system performance along dimensions relevant to safety and identify long-pole subsystem behavior for targeted development
- Exploratory timeseries analysis
- Training and deployment of temporal pattern recognition systems
- Design of internal tools to streamline both system and subsystem validation
- PhD (or 5+ years experience) in Computer Science, Engineering, Math, or a similar field
- Excellent communication skills
- Proven experience with statistical modeling (e.g. regression)
- Experience with Spark
- Experience with time series data streams
- Implementation experience in both supervised and unsupervised ML methods
- Prior experience with kinematic data streams
- Prior experience with scene analysis
- Prior experience in a related robotics or autonomy discipline
- Solve difficult problems that have immediate and valuable real-world applications
- Competitive salary and benefits including matched 401k, medical / dental / vision, AD+D and Life
- Flexible vacation and 10 paid company holidays
- State of the art equipment for your work station
- Lunch, snacks, and dinner
- Free rides in self-driving cars!
GM Cruise LLC provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, veteran status, or genetics. In addition to federal law requirements, GM Cruise LLC complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.