Senior Site Reliability Engineer, DGX Cloud

NVIDIA; Zürich; Vor Ort; CHF 180.000 - 240.000; Vollzeit

Zusammenfassung

NVIDIA in Zürich seeks an experienced Senior Site Reliability Engineer to maintain and scale DGX Cloud clusters for AI researchers and enterprise clients worldwide.

You will define SLOs, build observability stacks, automate infrastructure, and lead on-call incidents across multiple clouds, ensuring high reliability and velocity.

The role requires 10+ years of production experience, deep Kubernetes expertise, and strong programming skills in Python or Go.

Qualifikationen

• BS in Computer Science or related technical field, or equivalent experience.
• 10+ years of experience operating production services.
• Expert-level knowledge of Kubernetes administration, containerization, and microservices.
• Experience with infrastructure automation tools (Terraform, Ansible, Chef, Puppet).
• Proficiency in Python or Go.
• Deep knowledge of Linux, TCP/IP, and cloud security.
• Strong SRE fundamentals: SLOs/SLIs, error budgets, incident handling.
• Experience with observability stacks: OpenTelemetry, Prometheus, Grafana, ELK, Splunk.

Aufgaben

• Build, deploy and support large-scale Kubernetes clusters with emphasis on performance and reliability.
• Define SLOs/SLIs and monitor error budgets, reporting outcomes.
• Develop tools and automation for capacity planning and launch reviews.
• Maintain live services by measuring availability, latency, and health.
• Operate GPU workloads across cloud providers and private clouds.
• Lead triage and root-cause analysis of high-severity incidents.
• Participate in on-call rotations and conduct blameless postmortems.

Kenntnisse

Kubernetes

SRE principles

Observability

Ausbildung

BS in Computer Science or related field

Tools

Terraform

Ansible

Chef

Puppet

OpenTelemetry

Prometheus

Grafana

ELK Stack

Lightstep

Splunk

Jobbeschreibung

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology—and amazing people.

Today, we're 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 what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.

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 you’ll be doing:

• Build, implement and support operational and reliability aspects of large-scale Kubernetes clusters with focus on performance at scale, real time monitoring, logging and alerting

• Define SLOs/SLIs, monitor error budgets, and streamline reporting

• Support services before they launch through system creation consulting, developing software tools, platforms and frameworks, capacity management, and launch reviews

• 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

• 10+ years of experience operating production services

• Expert-level knowledge of Kubernetes administration, containerization, and microservices architecture

• 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

• 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, etc.

Ways to stand out from the crowd:

• Operating GPU-accelerated clusters with KubeVirt in production

• Applying generative-AI techniques to reduce operational toil

• Experience with workflow orchestration platforms such as Temporal, Cadence, Airflow, Argo Workflows, or Step Functions