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Senior Software Engineer - Kubernetes AI Scheduler

NVIDIANVIDIA·Semiconductors

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Posted

48 days

Sponsorship

H-1B history

This company has a track record of sponsoring H-1B visas.

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About the role

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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Aplyr's read

NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.

Synthesized from recent postings & public sources

What's promising

  • NVIDIA leads the GPU market, crucial for gaming and AI applications.
  • The company invests heavily in AI and deep learning, driving technological advancements.
  • NVIDIA's strong market position offers stability and growth opportunities for employees.

What to watch

  • High competition in the semiconductor industry can impact market share.
  • Rapid technological changes require constant adaptation and learning.
  • Intense workload and high expectations may affect work-life balance.

Why NVIDIA

  • NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
  • The company's AI research is at the forefront of deep learning innovation.
  • NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.

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About NVIDIA

NVDA$224.09+3.03%

NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.

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