Senior Software Engineer - Kubernetes AI Infrastructure
Nvidia
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This role on the market
2,106 open infrastructure roles across 275 companies are on ApplySarthi right now, most of them in Bengaluru (70), Hyderabad (30), Mumbai (12).
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What infrastructure roles keep asking for: AWS (32%), Python (26%), Kubernetes (23%), System design (22%), Observability (22%), Terraform (17%), CI/CD (16%), Linux (15%) — counted across their open postings here.
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Nvidia has 2,445 open roles listed here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for infrastructure roles keep coming back to AWS, Python, Kubernetes, System design. 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.
- What would you check first if a model's accuracy dropped after going live?
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
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Practise the Senior Software Engineer - Kubernetes AI Infrastructure at Nvidia interview free →KAI-Scheduler is an open-source CNCF project focused on delivering the best scheduling experience for AI workloads on Kubernetes. Adopted by AI frontier labs, leading enterprises, and some of the largest AI infrastructure deployments in the world, KAI helps organizations efficiently run AI at scale. KAI is designed to support any AI infrastructure—from the latest GPU and networking technologies to future hardware generations—while maximizing performance, utilization, and scalability. As a Senior Software Engineer for KAI, you will help build the future of AI scheduling in the Kubernetes ecosystem, working on challenging problems spanning workload scheduling, Kubernetes internals, and large-scale AI infrastructure. What you’ll be doing: Develop clean, maintainable, and well-tested software in Go. Design and implement scalability improvements for KAI, helping it operates efficiently in massive-scale deployments (thousands of nodes) while addressing Kubernetes scaling constraints and bottlenecks. Apply strong algorithmic thinking to solve complex AI workload scheduling and placement challenges, balancing performance, fairness, cluster utilization, topology constraints, and scalability. Conduct code and design reviews to uphold high-quality standards and mentor team members. Work closely with contributors, users, and customers, helping translate feedback from production deployments into product and engineering improvements. Collaborate with related upstream projects (schedulers, AI frameworks, cluster autoscalers, Kubernetes SIGs/WGs, etc.) and contribute to community and ecosystem discussions. What we need to see: B.Sc. or M.Sc. in Computer Science or a related field or equivalent experience 8+ years of experience in backend software development, including system design and architecture 4+ years of advanced Kubernetes development experience, including designing and implementing CRDs and controllers, with deep expertise in Kubernetes internals, networking, storage, and cluster architecture. Strong algorithmic skills with experience tackling complex optimization and distributed systems challenges. Strong technical skills and a proven ability to collaborate with and mentor other engineers. We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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Listed on workday · posted 2026-10-06. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.