Senior Software Engineer – Kubernetes AI Foundations Open Source
Nvidia
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What foundations roles keep asking for: AWS (32%), Python (29%), Java (29%), LLMs (29%), Machine learning (27%), Observability (24%), PyTorch (21%), C++ (20%) — counted across their open postings here.
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Preparing for this interview
Interviews for foundations roles keep coming back to AWS, Python, Java, LLMs. Practise those questions before you sit with Nvidia.
Questions you are likely to be asked
- Why do you want to join Nvidia?
- What is your experience with Kubernetes? Tell me one thing you learned the hard way.
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
- Tell me about a time the data was messy or wrong. What did you do?
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Practise the Senior Software Engineer – Kubernetes AI Foundations Open Source at Nvidia interview free →NVIDIA is building the software foundation for the next generation of AI infrastructure. As AI workloads continue to evolve, Kubernetes and the cloud-native ecosystem must evolve with them. Our team’s mission is to make Kubernetes the best platform for AI workloads. We work upstream with the Kubernetes and CNCF communities to design new APIs, build production-grade implementations, and shape the future of cloud-native infrastructure for AI. As a Senior Software Engineer, you'll tackle the most challenging problems at the intersection of Kubernetes, distributed systems, and AI infrastructure. What you'll be doing Design, implement, and upstream new capabilities for Kubernetes and CNCF projects. Collaborate with engineering teams across NVIDIA to identify AI infrastructure challenges and solve them through upstream innovation. Work closely with Kubernetes SIGs, Working Groups, and the broader open-source community to design and implement new capabilities. Participate in architecture discussions, API design, technical proposals, and code reviews. Build reliable, scalable infrastructure software for next-generation AI workloads. Write clear technical documentation and design proposals. What we need to see B.Sc/M.Sc or higher in Computer Science, Computer Engineering, or a related field or equivalent practical experience. 5+ years of software engineering experience building distributed systems, cloud infrastructure, or platform software. Deep understanding of Kubernetes and the cloud-native ecosystem. Experience extending, building, or contributing to Kubernetes-based solutions. Strong communication skills and the ability to collaborate across engineering teams and open-source communities. Curiosity, adaptability, and an interest in learning AI infrastructure. Ways to stand out from the crowd Active contributor to Kubernetes, CNCF, or other open-source infrastructure projects. Leadership experience in open-source communities, such as maintainer, reviewer, approver, SIG/WG leadership, or similar roles. Experience designing Kubernetes APIs, authoring KEPs, or driving community proposals through upstream processes. Experience with Kubernetes scheduling, networking, Gateway API, workload APIs, or other core Kubernetes subsystems. Understanding of AI infrastructure, including inference systems, GPU scheduling, distributed serving, or LLM infrastructure. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered one of the technology world's most desirable employers. We have some of the most forward-thinking engineers in the industry solving the hardest infrastructure problems at global scale. If you're excited about building the future of Kubernetes through open source and enabling the next generation of AI infrastructure, we'd love to hear from you.
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Listed on workday · posted 2026-10-15. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.