We are looking for a highly motivated k8s AI infrastructure engineer to join our team in the fastest growing organization at NVIDIA. There is an excellent opportunity to architect and drive advancements in the SRE automation on the largest GPU cluster at NVIDIA ! Please apply if you are passionate about Kubernetes, building infrastructure automation and deployment tooling and working on new technologies and Cloud Native applications.

What you 'll be doing:

As part of Maglev 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 Autonomous Vehicles products team!
Driving a new SRE automation tooling development for the onprem and cloud based k8s clusters
Proposing new ways to improve observability and alerting for the MLOPS AI infrastructure
Helping team to address increasing scale of the computing k8s clusters and enable more efficient configuration management

What we need to see:

BS or MS in CS/CE/EE or equivalent experience
3+ years of the k8s experience on-prem and in the AWS
4+ years building automation software APIs for the large scale computing clusters and data platforms
Versatility with at least one programming languages like: Go, Python
Complete understanding of the Kubernetes and Cloud Native Architecture
Experience deploying services onprem/cloud and managing them
Deep knowledge of the networking fundamentals
Expertise at problem solving and complexity analysis of the distributed systems
Proficiency with Linux environment
Excellent written and verbal social skills

Ways to stand out from the crowd:

Help our team to develop a better stack of Go and Python automation APIs
You are a meticulous organizer with an ever positive, can-do attitude
Demonstrate use of out-of-box thinking for creative solutions to highly sticky problems
You'll be a fun and hardworking teammate who enjoys a challenge and celebrates success
Working experience with k8s observability - Prometheus/Grafana, ELK
Previous experience with building sophisticated tooling and SRE automation on the large 100+ nodes GPU and CPU clusters
Building automated and scalable infrastructure for the data services like Redis, MongoDB, Kafka, Spark and ElasticSearch
You have extensive experience across wide range of Observability solutions

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 daring problems in everyday life.

The base salary range is $141,000 - $325,000. 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](https://www.nvidia.com/en- us/benefits/).

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.

Senior Site Reliability Engineer - AI Infrastructure