Senior Systems Software Engineer, Kubernetes Scale - DGX Cloud
NVIDIA France · PLN 292K–PLN 650K/yr
Computer Hardware Manufacturing · 10,001+ employees
About the role
Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack across Kubernetes and hardware components. Collaborate with researchers and developers to build automated testing frameworks and resolve complex performance issues in distributed systems.
What they look for
Requirements
Requires 8+ years of experience in computer architecture, networking, and distributed systems with expertise in Kubernetes. Candidates must possess a degree in engineering or computer science and proficiency in Golang or Python.
Full 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.
Similar roles
-
Senior Kubernetes Software Engineer
IP Secure, LLC San Antonio, Texas, United States
-
Lead Kubernetes Platform Engineer
3M Saint Paul, Minnesota, United States · $146K–$178K/yr
-
Principal Kubernetes Platform Engineer
Mastercard New York, New York, United States · $170K–$323K/yr
-
Product Owner Expert - Kubernetes, CaaS Platform
PNC Birmingham, Alabama, United States · $133K–$296K/yr
-
Platform Engineer (Kubernetes)
Clera San Francisco, California, United States · $180K–$210K/yr
-
Mise en œuvre d'un déploiement automatisé sur un cluster Kubernetes F/H
Orange SA Caen, Normandy, France