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.
Our Infrastructure team is building a highly resilient, performant, and secure internal Platform as a Service which hosts our core backend services to control our fleet of vehicles, runs driving simulations at scale, and executes machine learning training jobs for our Autonomous Vehicle engineering team. We’re currently using AWS, Docker, Kubernetes, Vault, and Spinnaker, but we’re also interested in your experience and suggestions.
- Build and maintain storage system capable of ingesting hundreds of terabytes per day and storing hundreds of petabytes for analysis
- Interface with a scalable data pipeline to handle processing of large amounts of sensor and vehicle log data
- Architect, design and tune our systems to keep ahead of our developers and scientists need for data
- Expert level knowledge of large scale (10+ PB) storage systems (distributed filesystems, object stores, etc.) such as GlusterFS, OpenStack Swift, or AWS S3
- Experience managing physical compute, storage, and networking hardware
- Experience with Kubernetes, or other container orchestration tools
- Familiarity with ROS
- Experience managing, monitoring and capacity planning large scale storage systems with aggressive ingestion and long retention requirements (TBs/day)
- 5+ years of professional experience in systems engineering in large scale Linux/UNIX data center environments
- Solid understanding of how to configure, deploy, manage and maintain large cloud hosted systems; including auto-scaling, monitoring, performance tuning, troubleshooting and disaster recovery.
- Experience delivering on strategic initiatives effectively in a fast paced environment while supporting day-to-day issues
- In depth, hands-on experience with Linux, networking, server, and cloud architectures.
- Knowledge of metrics & monitoring (e.g., Splunk, Nagios etc.) and configuration management tools (e.g., Chef, Puppet, etc.).
- Deep understanding of network technologies like DNS, Load Balancing, SSL, TCP/IP, SQL, HTTP.
- BS in CS or any engineering discipline or equivalent experience
• Experience programming with Python, Go (golang), Node, C++, or similar
• Experience with software based compute infrastructure such as AWS, Azure, GCE, OpenStack, CoreOS
• Proficiency with source control, continuous integration, and testing pipelines.
• Experience with container orchestration systems such as Kubernetes or Docker
• Experience with resource Management systems such as Borg, Mesos, Aurora, Marathon, Yarn
• Expertise in live site operations for stateful services, such as Hadoop, HBase
- 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
- Paid parental leave
- 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. Applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.