NVIDIA
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Its a unique legacy of innovation thats fueled by great technologyand amazing people. Today, were tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing whats never been done before takes vision, innovation, and the worlds best talent. As an NVIDIAN, youll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
NVIDIA is driving AI and high-performance computing forward. DGX Cloud aims to deliver a fully managed AI platform on major cloud providers, optimizing AI workloads using high-performance NVIDIA infrastructure. Work with NVIDIA's DGX Cloud team as a Senior Site Reliability Engineer to maintain high-performance DGX Cloud clusters for AI researchers and enterprise clients worldwide.
What youll be doing:
Support large-scale Kubernetes services before they launch through system creation consulting, developing software tools, platforms,, and frameworks, capacity management, and launch reviews
Build, implement and support operational and reliability aspects of large-scale Kubernetes clusters with a focus on performance at scale, real-time monitoring, logging and alerting
Define SLOs/SLIs, monitor error budgets, and streamline reporting
Maintain services once they are live by measuring and monitoring availability, latency, and overall system health
Operate and optimize GPU workloads across AWS, GCP, Azure, OCI, and private clouds
Scale systems sustainably through mechanisms like automation and evolve systems by pushing for changes that improve reliability and velocity
Lead triage and root-cause analysis of high-severity incidents
Practice balanced incident response and blameless postmortems
Participate in on-call rotation to support production services
What we need to see: BS in Computer Science or related technical field, or equivalent experience
12+ years of experience operating production services at scale
Expert-level knowledge of Kubernetes administration, containerization, and microservices architecture, with deep experience in Kubernetes operators and distributed systems at scale.
Experience with infrastructure automation tools (e.g., Terraform, Ansible, Chef, Puppet)
Proficiency in at least one high-level programming language (e.g., Python, Go)
In-depth knowledge of Linux operating systems, networking fundamentals (TCP/IP), and cloud security standards
Demonstrated ability to troubleshoot complex DNS, network, Kubernetes, and systems issues in production environments.
Proficient knowledge of SRE principles, encompassing SLOs, SLIs, error budgets, and incident handling
Experience building and operating comprehensive observability stacks (monitoring, logging, tracing) using tools like OpenTelemetry, Prometheus, Grafana, ELK Stack, Lightstep, Splunk, Datadog, etc.
Ways to stand out from the crowd: Operating GPU-accelerated clusters with KubeVirt in production
Applying generative-AI techniques to reduce operational toil
Automating incidents with Shoreline or StackStorm
GPU workload orchestration and large-scale GPU resource management
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and versatile people in the world working with us, and our engineering teams are growing fast in some of the most impactful fields of our generation: Cloud Engineering, Cloud Infrastructure, and Site Reliability Engineering. If you're a creative engineer who enjoys autonomy and shares our passion for technology, 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. The base salary range is 208,000 USD - 333,500 USD.
You will also be eligible for equity and benefits. Applications for this job will be accepted at least until September 6, 2025. 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.
Build, implement and support operational and reliability aspects of large-scale Kubernetes clusters with a focus on performance at scale, real-time monitoring, logging and alerting
Define SLOs/SLIs, monitor error budgets, and streamline reporting
Maintain services once they are live by measuring and monitoring availability, latency, and overall system health
Operate and optimize GPU workloads across AWS, GCP, Azure, OCI, and private clouds
Scale systems sustainably through mechanisms like automation and evolve systems by pushing for changes that improve reliability and velocity
Lead triage and root-cause analysis of high-severity incidents
Practice balanced incident response and blameless postmortems
Participate in on-call rotation to support production services
What we need to see: BS in Computer Science or related technical field, or equivalent experience
12+ years of experience operating production services at scale
Expert-level knowledge of Kubernetes administration, containerization, and microservices architecture, with deep experience in Kubernetes operators and distributed systems at scale.
Experience with infrastructure automation tools (e.g., Terraform, Ansible, Chef, Puppet)
Proficiency in at least one high-level programming language (e.g., Python, Go)
In-depth knowledge of Linux operating systems, networking fundamentals (TCP/IP), and cloud security standards
Demonstrated ability to troubleshoot complex DNS, network, Kubernetes, and systems issues in production environments.
Proficient knowledge of SRE principles, encompassing SLOs, SLIs, error budgets, and incident handling
Experience building and operating comprehensive observability stacks (monitoring, logging, tracing) using tools like OpenTelemetry, Prometheus, Grafana, ELK Stack, Lightstep, Splunk, Datadog, etc.
Ways to stand out from the crowd: Operating GPU-accelerated clusters with KubeVirt in production
Applying generative-AI techniques to reduce operational toil
Automating incidents with Shoreline or StackStorm
GPU workload orchestration and large-scale GPU resource management
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and versatile people in the world working with us, and our engineering teams are growing fast in some of the most impactful fields of our generation: Cloud Engineering, Cloud Infrastructure, and Site Reliability Engineering. If you're a creative engineer who enjoys autonomy and shares our passion for technology, 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. The base salary range is 208,000 USD - 333,500 USD.
You will also be eligible for equity and benefits. Applications for this job will be accepted at least until September 6, 2025. 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.