Posted:
10/9/2024, 5:00:00 PM
Location(s):
District of Columbia, United States ⋅ Washington, District of Columbia, United States ⋅ Oregon, United States ⋅ California, United States
Experience Level(s):
Mid Level ⋅ Senior
Field(s):
AI & Machine Learning
Workplace Type:
Remote
We are looking for a highly motivated k8s AI infrastructure generalist to join our team in the one of the most expert k8s organization. There is an excellent opportunity to architect and drive advancements in the SRE automation on the largest NVIDIA GPU clusters in the cloud! Please apply if you are passionate about Kubernetes, building k8s infrastructure automation and deployment tools and working on new technologies and Cloud Native applications.
What you'll be doing:
As part of Maglev AI infrastructure and SRE team you will propose and craft new ways to improve availability of our Cloud Native AI Platform by automating critical processes on the multiple distributed GPU clusters
The solutions you propose and build will impact directly efficiency of the NVIDIA Autonomous Vehicles Perception development team!
What we need to see:
BS or MS in the CS/CE/EE or equivalent experience
At least 6+ years of the k8s experience on-prem and in the cloud
At least 4 years building automation software APIs for the large scale computing clusters and data platforms
You can help our team to develop a better stack of Go and Python automation APIs
Complete understanding of the Kubernetes and Cloud Native Architecture and working experience with k8s clusters
Expertise at problem solving and complexity analysis of the distributed systems
Proficiency with Linux environment
Excellent written and verbal interpersonal skills
You'll be a fun and motivated teammate who enjoys a challenge and celebrates success
Ways to stand out from the crowd:
Previous experience with building sophisticated tooling and SRE automation on the large 100+ nodes GPU/CPU clusters
DevSecOps experience with good understanding of the cloud security concepts
Deep knowledge of the networking layers and fundamentals
For two decades, we have pioneered visual computing, the art and science of computer graphics. With our invention of the GPU - the engine of modern visual computing - the field has expanded to encompass video games, movie production, product design, medical diagnosis and scientific research. Today, we stand at the beginning of the new AI computing era, ignited by a new computing model, GPU deep learning. This new model - where deep neural network is trained to recognize patterns from extensive amounts of data - has shown to be deeply effective at solving some of the most adventurous problems in everyday life.
The base salary range is 180,000 USD - 339,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Website: https://www.nvidia.com/
Headquarter Location: Santa Clara, California, United States
Employee Count: 10001+
Year Founded: 1993
IPO Status: Public
Last Funding Type: Grant
Industries: Artificial Intelligence (AI) ⋅ GPU ⋅ Hardware ⋅ Software ⋅ Virtual Reality