NVIDIA

Senior Site Reliability Engineer in Test, SDET

NVIDIA Shanghai, Shanghai, China

Computer Hardware Manufacturing · 10,001+ employees

13 h ago
sre Senior (5-10 yrs) Full-time China
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About the role

Design, build, and operate scalable test environments and CI/CD infrastructure to support the validation of NVIDIA enterprise offerings. Implement reliability practices such as SLIs/SLOs, chaos engineering, and automated remediation to ensure high-quality software delivery.

What they look for

Site Reliability Engineering Test Environment Management CI/CD Kubernetes Python Linux GitLab CI GitHub Actions ArgoCD Docker Automation Software Testing Infrastructure as Code Vulnerability Management Distributed Systems AI/ML

Requirements

Requires a Master's or PhD in Computer Science or equivalent with at least 8 years of professional experience in SRE, CI/CD, or test infrastructure. Candidates must possess strong proficiency in Linux, Python, containerization, and modern GitOps workflows.

Full description

At NVIDIA, we are at the forefront of technological innovation, pushing the boundaries of AI and accelerated computing. Our team in Shanghai, China is looking for a Senior Site Reliability Engineer focused on Test Environment Management to join us. This is an opportunity to build and operate highly reliable test infrastructure, CI/CD systems, and environments that power validation of NVIDIA enterprise offerings. If you are passionate about reliability engineering, test infrastructure, and AI-scale systems, this role is for you.

What you’ll be doing

  • Design, build, operate, and continuously improve reliable, scalable test environments and automation infrastructure that support validation of NVIDIA enterprise offerings.
  • Own end-to-end CI/CD pipelines using GitLab CI, GitHub Actions, and ArgoCD (GitOps) — including pipeline design, reliability, performance, and progressive delivery of test workloads.
  • Manage Software Bills of Materials (SBOMs): generation, continuous monitoring, vulnerability correlation, policy enforcement, and integration into CI/CD and release gate..
  • Provision, scale, observe, and lifecycle-manage ephemeral and long-lived test environments (Kubernetes-based and hybrid) with strong emphasis on isolation, reproducibility, and rapid recovery.
  • Define and drive reliability practices for test systems: SLIs/SLOs/error budgets for test environments and pipelines, toil reduction, chaos/resilience testing of infrastructure, and automated remediation.
  • Collaborate closely with development and platform teams to triage environment and pipeline failures, perform root-cause analysis, verify fixes, and continuously harden test infrastructure.
  • Apply AI/ML/Agentic techniques and internal tools to accelerate environment provisioning, flaky-test detection, capacity planning, anomaly detection, and overall Quality Assurance velocity.

What we need to see

  • MS or PhD in Computer Science, related field, or equivalent experience with 8+ years of professional experience in Site Reliability Engineering, Test Environment Management, CI/CD platform engineering, or software testing infrastructure.
  • Strong proficiency with Linux, shell scripting, and Python (or equivalent automation languages).
  • Hands-on experience designing and operating CI/CD systems with GitLab CI and/or GitHub Actions, practical experience with ArgoCD (or equivalent GitOps tooling) for CD of applications and infrastructure. Solid background in containerization and orchestration (Docker, Kubernetes) and virtualization technologies.
  • Deep understanding of SRE principles: SLIs/SLOs, error budgets, incident response, postmortems, toil elimination, and reliability engineering for complex distributed systems.
  • Experience building and operating test environments (ephemeral, multi-tenant, or production-like) with focus on reliability, isolation, and rapid turnaround.
  • Strong knowledge of QA principles and how test infrastructure enables high-quality software delivery.
  • Comfort working with AI/LLM-related workloads and toolings. Excellent problem-solving skills, clear written and verbal communication, and the ability to collaborate across engineering teams.
  • Self-motivated, proactive, and passionate about learning new technology at scale.

Ways to stand out from the crowd

  • Experience operating large-scale Kubernetes platforms and GitOps workflows in production or high-stakes test environments.
  • Background in software supply-chain security, SBOM tooling ecosystems, vulnerability management, and policy enforcement (OPA/Gatekeeper, Kyverno, etc.).
  • Hands-on work with NVIDIA GPU hardware, multi-GPU environments, or accelerated computing infrastructure. Experience with parallel programming, high-performance computing, or large-scale AI model training/inference test harnesses.
  • Track record of applying AI/observability techniques to detect flaky tests, optimize environment utilization, or automate root-cause analysis.
  • Prior experience defining and driving reliability programs (error budgets, chaos engineering, capacity forecasting) for CI/CD or test platforms.

NVIDIA is widely considered one of the technology world’s most desirable employers. We have some of the most brilliant people on the planet working for us. If you’re creative, autonomous, and excited about making test infrastructure as reliable as the products it validates, we want to hear from you!

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