NVIDIA Corporation

Senior Systems Software Engineer, Accelerated Kubernetes Performance and Scale - DGX Cloud

NVIDIA Corporation$184K — $356K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's degree in Engineering or related field
  • 8+ years of experience in computer architecture, networking, storage systems, and accelerator-based platforms
  • Expertise in Kubernetes and familiarity with the CNCF ecosystem
  • Deep experience with large-scale, parallel, distributed accelerator systems
  • Experience with performance modeling for large-scale systems
  • Proficiency in Golang and/or Python
  • Strong familiarity with NVIDIA software stack for training and inference
  • Expertise with at least one major public cloud provider (AWS, Azure, GCP, OCI)

Responsibilities

  • Lead performance and scalability analysis across the Kubernetes-based accelerated runtime stack
  • Design architectural changes to Kubernetes control plane for hyperscale operations
  • Improve container startup and cold-start latency for low-latency inference
  • Contribute to open-source projects enhancing Kubernetes for AI workloads
  • Advance scalability of confidential containers on Kubernetes for encrypted workloads
  • Model AI-factory deployments and validate scalability using large-scale simulations
  • Collaborate to design automated workload tests and integrate performance testing into CI/CD workflows
  • Document methods and present results internally and at industry events

Benefits

  • Opportunity to work on cutting-edge AI infrastructure
  • Engage with a team of forward-thinking engineers
  • Impactful role shaping AI workloads in production
  • Collaboration with AI researchers and developers
  • Involvement in the open-source community
  • Hybrid work environment offering flexibility
  • Potential for equity and comprehensive benefits package
Full Job Description
The DGX Cloud organization at NVIDIA brings together cutting-edge hardware and software innovation to deliver industry-leading accelerated computing for the world's most ambitious AI workloads. We are a group of forward-thinking engineers tackling some of the globe's toughest challenges, pushing progress, and positively affecting millions of lives. We're searching for a Senior Systems Software Engineer with deep expertise in distributed systems, Kubernetes, containers, and systems performance and scalability. The ideal candidate brings broad, hands-on experience across the stack, including GPU operators, device plugins, distributed inference serving, and major cloud platforms. You'll own hard technical problems at large scale and help shape how AI infrastructure runs in production. In this key role, you will focus on scaling AI infrastructure while minimizing total cost of ownership, reducing cost per token and enabling future AI innovation and AI factories. Are you ready to be impactful? What you'll be doing:
  • Lead end-to-end performance and scalability analysis across the Kubernetes-based accelerated runtime stack (control and data planes), including NVIDIA components such as GPU Operator, Network Operator, node-feature-discovery, topograph, dra-driver-nvidia-gpu, and nvsentinel, tracking issues from orchestration down to the metal.
  • Design and contribute upstream architectural changes to the Kubernetes control plane and related projects to enable reliable operation at hyperscale cluster sizes, doing in the open what today's hyperscalers typically do privately.
  • Improve container startup and cold-start latency to enable smooth, low-latency inference scaling on Kubernetes across thousands of GPU nodes, ensuring the AI runtime stack scales without creating API server pressure or operational fragility.
  • Assess, improve, and contribute to open-source projects that make Kubernetes an outstanding platform for AI workloads (for example, Grove and gateway-api-inference-extension), composing their architectures with scalability, resilience, and multi-node training/inference in mind.
  • Advance scalability and performance of confidential containers (CoCo) on Kubernetes so encrypted inference workloads meet stringent efficiency and latency requirements in production.
  • Use DSX and related large-scale simulation infrastructure to model full AI-factory deployments and validate scalability across thousands of simulated GPUs, catching failures that emerge only at scale before hardware arrives.
  • Collaborate with AI researchers, developers, customers, and upstream communities to design automated, at-scale workload tests (including replay of production agent traces), build monitoring/analysis tooling, and integrate continuous performance and scale testing into modern CI/CD workflows.
  • Document methods and results clearly and present findings internally and at industry events (for example, KubeCon, GTC), while actively engaging with upstream groups (Kubernetes SIG Scalability, CNCF, and NVIDIA OSS communities) to influence and validate AI workload performance and scalability directions.
What we need to see:
  • Bachelor's or Master's degree in Engineering or equivalent experience, ideally in Electrical, Computer Engineering, or Computer Science
  • 8+ years of experience in computer architecture, networking, storage systems, and accelerator-based platforms
  • Expertise in Kubernetes and familiarity with the broader CNCF ecosystem
  • Deep experience with large-scale, parallel, distributed accelerator systems and performance optimization of AI workloads
  • Experience with performance modeling and benchmarking for large-scale systems
  • Proficiency in Golang and/or Python
  • Strong familiarity with the NVIDIA software stack across training and inference
  • Expertise with at least one major public cloud provider (for example, AWS, Azure, GCP, or OCI)
Ways to stand out from the crowd:
  • Strong operational experience with any one of the Kubernetes distributions
  • Prior experience scaling Kubernetes clusters to ultra-large node and object counts
  • Demonstrated history of working in the open-source community
  • Excellent communication and interpersonal abilities
  • PhD or equivalent experience in relevant areas
#LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until June 29, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ

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