What to Expect
As a member of the Dojo Reliability and Test team, you will support engineering’s effort to identify and characterize hardware failure modes in Tesla’s Dojo Supercomputer.
You will be responsible for delivering robust, modular, and easy to use code that enables rapid and efficient deployment of new tests and test systems.
Tesla is continuously launching new products at a rapid pace and you will work directly with development teams across the organization to ensure that our new products are best in class.
We are interested in diverse candidates with all levels of experience, but we will prioritize curious and driven engineers with strong problem solving, communication, and collaboration skills.
What You’ll Do
Build tools for storage, retrieval, and visualization of test data from MongoDB, Prometheus, and Grafana frameworks
Write Python code to automate control of equipment
Manage infrastructure using Docker and Kubernetes
Enable test engineers to access their data using a React web front-end
Provide REST endpoints to serve test data to be consumed by that web front-end or by engineers’ custom Python scripts
Disseminate improved software throughout the test lab to elevate other testing.
You will train engineers, technicians, and interns to operate your new tools and drive their adoption
Directly receive and implement user feedback, iterating quickly to provide useful, well-received tools
What You’ll Bring
Fluent in system-level languages such as Python, C, C++.
Experience with Linux, Docker, Bash, and Git
Experience developing or working with CI/CD pipelines
Strong understanding of computer networks
Proficiency using React, TypeScript, or other front-end design languages/tools
Experience with data structures, architectures, and languages such as SQL and MongoDB
Versed in software fundamentals including software systems design and maintainability
Experience with full-stack development
Ability to collaborate and communicate technical concepts to those in non-software roles
Interest in solving complex and time critical problems