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 Principal Engineer for KAI, you will drive the technical direction of the project and shape the future of AI scheduling in the Kubernetes ecosystem.
What you’ll be doing:
- Define the technical roadmap of KAI-Scheduler, driving its architecture, APIs, extensibility, performance, and long-term direction, ensuring alignment with the evolving Kubernetes ecosystem.
- Drive the scalability strategy of KAI for massive-scale deployments (thousands of nodes and tens of thousands of GPUs), with deep understanding of 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.
- Engage directly with contributors, users, and customers, incorporating feedback from real-world production deployments into the project's technical direction and serving as a visible technical leader within the open-source community.
- Proactively collaborate with related upstream projects (schedulers, AI frameworks, cluster autoscalers, Kubernetes SIGs/WGs, etc.) and represent KAI in community and ecosystem discussions.
What we need to see:
- B.Sc. or M.Sc. in Computer Science or a related field or equivalent experience
- 15+ years of experience in backend software development, including system design and architecture, include 6+ 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 background with experience solving complex optimization and distributed systems problems.
- Superb technical level and a proven ability to mentor other engineers through code reviews, design reviews, and technical leadership.
- Experience in maintaining open-source projects in the Kubernetes or broader cloud-native ecosystem, with a strong understanding of healthy open-source project dynamics, contributor engagement, and community collaboration.
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.
Skills Required
- B.Sc. or M.Sc. in Computer Science or related field or equivalent experience
- 15+ years of backend software development experience including system design and architecture
- 6+ years of advanced Kubernetes development experience, including designing and implementing CRDs and controllers
- Deep expertise in Kubernetes internals, networking, storage, and cluster architecture
- Strong algorithmic background solving complex optimization and distributed systems problems
- Proven ability to mentor engineers via code reviews, design reviews, and technical leadership
- Experience maintaining open-source projects in the Kubernetes or cloud-native ecosystem and contributor/community engagement
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
