Senior Site Reliability Engineer - GPU Cloud

Reposted 17 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka
In-Office
8-8
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Responsible for managing the infrastructure of NVIDIA's GPU cloud, ensuring reliability and availability, and providing scalable automation solutions.
Summary Generated by Built In

NVIDIA has been a pioneer in Accelerated Computing and has been paving the way with innovations in Generative AI, Large Language Model (LLM), Autonomous Vehicles, Robotics, High-Performance Computing (HPC), Gaming/Visualization, and Edge/Data Center/Cloud Computing. NVIDIA provides automakers, research institutions, cloud providers, large companies and start-ups the power and flexibility to develop and deploy breakthrough artificial intelligence systems.

We are a fast paced, dynamic and dedicated Site Reliability Engineering (SRE) team serving the forefront of the latest science and technology trends on cloud and on-prem infrastructure management for High-Performance & Distributed Computing. Working closely with the development teams, we provide hosted solutions for our internal and external customers. Are you passionate about infrastructure and enjoy working on and resolving intricate multi-faceted issues? Are you eager to have your hands on the engines of the next generation of cloud services? Do you get a buzz from identifying and eliminating toil, designing and coding innovative solutions that address the needs of a whole organization? If so, read on and give us a shout.

What you'll be doing:

The NVIDIA GPU cloud is a hosted platform for internal R&D teams and external AI/ML stack customers. This SRE team is accountable for the setup, management, reliability and availability of this infrastructure spanning 1000s of GPU nodes. As a senior SRE, you are responsible for:

  • Providing scalable and robust service oriented infrastructure automation, monitoring and analytics solutions for NVIDIA's on-prem and cloud based GPU infrastructure.

  • You will own the whole life cycle of new tools and services - from requirements gathering, to design documentation, validation and deployment.

  • Provide customer support on a rotation basis.

What we need to see:

  • Minimum of 8 years of experience ce in automating and handling large-scale distributed system software deployments in on-prem/cloud environments.

  • Proficiency in any language - Go/Python/Perl/C++/Java/C.

  • Strong command on terraform, Kubernetes and cloud infra administration.

  • Excellent debugging and troubleshooting skills.

  • Ability to design simple and reliable systems that can work without much support.

  • Outstanding teammate who can collaborate and influence in a multifaceted environment.

  • Excellent interpersonal, and written communication skills.

  • M.Sc or B.E in Computer Science or a related technical field involving coding (e.g., physics or mathematics)

Ways to stand out from the crowd:

  • Ability to decompose complex requirements into simple tasks and reuse available solutions to implement most of those.

  • Proven record of maintaining platform SLAs through accurate resolutions.

  • Unit testing and benchmarking are an integral part of your code.

  • Ability to reason and choose the best possible algorithm to meet scaling and availability challenges.

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!

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

C
C++
Cloud Infrastructure
Go
Java
Kubernetes
Perl
Python
Terraform
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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