Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Ansible @ 4
Go @ 7
Grafana @ 4
Kubernetes @ 4
Linux @ 4
Prometheus @ 4
IaC @ 4
Terraform @ 4
Python @ 7
GitHub @ 4
GitHub Actions @ 4
Bash @ 7
Helm @ 4
SRE @ 4
Microservices @ 7
Android @ 4
API @ 4
OpenTelemetry @ 4
GPU @ 4
Deep Learning @ 4
Observability @ 4
AI @ 4
Robotics @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is seeking a passionate, motivated, and technical Engineer to join its Infrastructure, Planning, and Processes organization as a Senior SRE Engineer. You will own and scale the company's internal CI as a Service platform, including shared GitLab CI and GitHub Actions infrastructure used by thousands of engineers. The role manages multi-OS and multi-hardware build and test environments (Windows, Linux, Android, NVIDIA GPUs, Tegra processors) and collaborates with software teams across graphics, mobile, deep learning, robotics, and autonomy.
Responsibilities
- Develop, operate, and scale a multi-tenant CI platform built on GitLab CI and GitHub Actions: runner fleets, shared caches, artifact storage, and secrets brokering.
- Own the Kubernetes substrate end-to-end: cluster lifecycle, upgrades, autoscaling, node pools for GPU/CPU/ARM workloads, network and storage policy, and operators/controllers that schedule runner pods on demand.
- Drive reliability and capacity engineering: define and manage SLOs/SLIs and error budgets for queue time, job success, and runner availability; participate in on-call, incident response, postmortems, and implement structural fixes to reduce toil.
- Build self-service layers: pipeline templates, reusable workflows, golden images, policy-as-code, and guardrails to enable fast, secure onboarding for product teams.
- Continuously improve developer experience: reduce cold-start times, optimize caching, enable hermetic builds, test sharding and flakiness reduction, and provide deep observability into pipeline performance and cost per team.
Requirements
- 5+ years in SRE/platform roles with strong fundamentals in SLO/SLI creation, incident command, resource planning, performance tuning, and production Linux administration at scale.
- Deep Kubernetes administration experience: CRDs and operators, HPA/VPA/cluster-autoscaling, ingress, service mesh, RBAC, network policies, storage classes, and advanced troubleshooting skills.
- Hands-on expertise with GitLab CI and GitHub Actions at scale: runner architecture, executor tuning, self-hosted runner controllers (ARC, GitLab-runner Helm chart), cache and artifact strategy, and pipeline development (DAGs or equivalent).
- Strong scripting and automation in Python, Go, and bash. Production experience with IaC/configuration management tooling such as Terraform, Helm, and Ansible.
- Experience with GitOps tools (Argo CD, Flux).
- BS/MS in Computer Science or equivalent experience. Experience building observability systems (Prometheus, Grafana, Loki/ELK, OpenTelemetry) and shipping platforms used by many engineers.
Ways to stand out
- Strong understanding of containerization and microservices architecture. Kubernetes certifications (CKA, CKS, CKAD) preferred.
- Experience building or extending CI control planes: custom runner schedulers, autoscaling, webhook routers, or orchestration on top of GitLab/GitHub APIs.
- Prior experience with large-scale operations teams, data center operations, and algorithmic approaches to scaling problems.
Compensation and benefits
- Base salary ranges provided by location/level: Level 3: 148,000 USD - 235,750 USD; Level 4: 176,000 USD - 276,000 USD.
- Eligible for equity and company benefits (link provided in original posting).
Additional information
- Applications accepted until July 6, 2026.
- NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer committed to inclusion.