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NVIDIA

Senior Systems Software Engineer, Kubernetes Scale - DGX Cloud

  • Remote
  • 6+ years

Salary

Not stated

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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 adventurous AI workloads. We're a team of innovative engineers dedicated to solving some of the world's biggest challenges, constantly driving advancements, and impacting millions of lives worldwide!

We are looking for an outstanding Senior Systems Software Engineer with deep experience in distributed systems, open-source technologies such as Kubernetes and containers, and a strong background in systems performance and scalability. The ideal candidate brings broad, end-to-end experience across the stack - from GPU operator and device plugins to distributed inference serving and cloud platforms - along with the technical depth to investigate and address exciting, real-world problems at scale. In this pivotal role, you will take on the challenge of scaling AI infrastructure while optimizing total cost of ownership, driving down cost per token to unlock the next generation of AI innovation and AI factories!

What you'll be doing:

Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack, from Kubernetes control and data planes through NVIDIA components such as GPU Operator, Network Operator, DCGM, NIM, and distributed inference serving, following issues from orchestration down to the metal.

Collaborate with AI researchers, developers and customers to develop innovative, automated tests that simulate real user workloads using custom-built and leading open-source tools and frameworks.

Deep dive into performance and scale issues in complex distributed systems, including interactions between Kubernetes and the NVIDIA software stack, to identify and resolve root causes.

Design and develop monitoring, reporting and analysis tools for performance and scale testing across software, GPU and CPU resources.

Triage, debug and root cause issues related to operating Kubernetes clusters at ultra-large scale, ensuring reliability and efficiency.

Build and maintain a high-velocity framework that enables continuous, always-on performance and scale testing via a modern CI/CD pipeline.

Document research, methodologies and results clearly and concisely, and present findings at internal and external venues, including community conferences such as KubeCon and GTC.

Engage efficiently with upstream communities — including Kubernetes, CNCF and NVIDIA open-source projects — to validate performance and scalability of AI workloads early and help shape design and development decisions.

What we need to see:

8+ years of experience Computer Architecture, Networking, Storage systems, Accelerators and Bachelors/Masters in Engineering (preferably, Electrical Engineering, Computer Engineering, or Computer Science) or equivalent experience

Expertise in Kubernetes and familiarity with related CNCF projects

Background in working with large scale parallel and distributed accelerator-based systems

Expertise optimizing performance and AI workloads on large scale systems

Experience with performance modeling and benchmarking at scale

Proficiency in Golang/Python

Background with the NVIDIA software ecosystem in both training and inference domains

Expertise with at least one of public CSP infrastructure (GCP, AWS, Azure, OCI for example)

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 in relevant areas

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. For Poland: The base salary range is 292,500 PLN - 507,000 PLN for Level 4, and 375,000 PLN - 650,000 PLN for Level 5.

Where you’d work

Fully remote

You can work from

  • Europe
  • United Kingdom
  • Spain
  • Poland
  • Switzerland
  • Germany
  • France

About the company

NVIDIA

Also hiring in United States, Munich, Germany, France and 14 more places

273 of their 660 open roles are remote

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Details11 facts · Role, Location, Compensation, Employment
Tech stack
  • Python
  • Go
  • AWS
  • Kubernetes
  • Azure
  • CI/CD
Seniority
Senior
Type
Full-time
Specialty
DevOps
Region
Europe
Pay period
Annual
Show 5 more factsShow less

Role

Category
DevOps & Infrastructure
Specialty
DevOps
Seniority
Senior
Experience
8+ years
Tech stack
  • Python
  • Go
  • AWS
  • Kubernetes
  • Azure
  • CI/CD

Location

Work model
Remote
Region
Europe
Remote from
  • Europe
  • United Kingdom

Compensation

Salary
Salary by agreement
Pay period
Annual

Employment

Type
Full-time

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