The Cloud team of the Development Infrastructure (DI) department is responsible for Mobileye's Cloud infrastructure on AWS and Google Cloud. We develop mainly in Python, and some Golang. We are developing highly efficient systems for the company, running on up to 700K CPUs, processing hundreds of Petabytes of data monthly collected from all the over the world. We also provide networking, security, governance, support and guidance for all of Mobileye's diverse uses of AWS across tens of AWS accounts, including AWS China.
What will your job look like?
Take part in the design, development, deployment, and maintenance of Mobileye's main cloud systems: Backend and python packages
Hyper-scale batch processing framework, spinning up hundreds of thousands of parallel computation CPU
Systems to ingest, store and manage data from cameras and other sensors, of exceptional volumes - 100 PB and more
Collaborate with different groups in Mobileye, including Algorithms, Software and Validation
Deliver a high quality product, fully developed by our team Work with highly experienced developers, architects and AWS experts.
Work tightly with AWS teams, bringing their services to the edge - S3, EC2, Spot, EBS, ECS, Batch, DynamoDB, CW
Build systems and tools using AWS Lambda, RDS, CloudFormation/Terraform and moreSee your product being used by hundreds of users, where every improvement, optimization and new feature can be critical to the development of autonomous vehicles and car safety systems.
All you need is:
B.Sc. in Computer Science / Engineering
At least 4-5 years of Python experience (experience with advanced Python packages)
Experience with backend: databases/Elastic Search/Redis, etc
Scale & Cloud: Strong hands-on experience developing and operating high-throughput, large-scale batch processing pipelines in AWS (e.g., AWS Batch, ECS/EKS, or Serverless).
Linux & Systems Fundamentals: Solid low-level Linux/OS background, including familiarity with memory management, system calls, process execution, binary inspection (e.g., ldd, strace, readelf), and performance troubleshooting.
Automation & Tooling: Proficient in system-level scripting and infrastructure automation, with a deep understanding of optimizing resource utilization (CPU, memory, storage) at scale.
Nive to Have:
Experience in high-scale systems.
Experience with Docker, Kubernetes, AWS Cloud Services.
Experience in Go.
