Join NVIDIA, a pioneer in technological innovation, where you will engage with a team that is reshaping the future of computing. As a Software and DevOps student, you will contribute alongside world-class engineers to develop groundbreaking solutions that affect our internal cloud scheduler and infrastructure management platform. This position offers a mix of software development and infrastructure responsibilities, presenting an outstanding chance for those wanting to sharpen their skills in both domains.
What you'll be doing:
- Building and supporting Python microservices that power our internal cloud scheduler and infrastructure management platform.
- Building software solutions for prioritisation, workload scheduling, infrastructure automation, and integrations with internal services.
- Crafting and maintaining Linux-based automation solutions for server provisioning, validation environments, and operational tooling.
- Working with brand new cloud and virtualization technologies including Docker, Kubernetes, and virtualized infrastructure environments.
- Participating in CI/CD workflows, automated testing, debugging, and deployment of software and infrastructure services.
- Collaborating with software developers, verification engineers, cloud engineers, and hardware teams to deliver scalable infrastructure solutions.
What we need to see:
- Currently pursuing a B.Sc. or an M.Sc. in Computer Science, Computer Engineering, Software Engineering, or a related field.
- Strong Python programming skills and understanding of software engineering fundamentals.
- Familiarity with Linux environments, scripting, and troubleshooting.
- Strong analytical, debugging, and problem-solving skills.
- Excellent communication skills and ability to work effectively in a team environment.
Ways to stand out from the crowd:
- Proven experience at managing, administrating and developing large scale, complex computing environments.
- Experience developing backend services, APIs, or microservice-based applications using Python.
- Familiarity with Docker, Kubernetes, CI/CD pipelines, or cloud-native technologies.
- Knowledge of Linux system administration, infrastructure automation, or DevOps practices.
- Experience with databases, distributed systems, or scheduling/resource management platforms.