Our team is looking for a Senior DevOps Engineer to join us and take ownership of the CI/CD infrastructure, automation pipelines, and development tooling that power our engineering teams. This position plays a key role in enabling fast, reliable, and scalable software delivery — from code commit to test execution and reporting. You will be the go-to expert for DevOps practices, collaborating closely with software engineers, validation teams, and infrastructure stakeholders across the organization.
What You'll Be Doing:
Design, implement, and maintain CI/CD pipelines for software and validation projects, ensuring fast, stable, and automated delivery workflows
Own and evolve the DevOps infrastructure — including build systems, artifact management, deployment automation, and environment provisioning
Develop and maintain automation tools, scripts, and integrations that streamline developer workflows and reduce manual overhead
Collaborate with validation, infrastructure, and software engineering teams to define and enforce DevOps best practices across the organization
Monitor system health, pipeline reliability, and build performance; identify bottlenecks and continuously improve observability and stability
Manage containerization and orchestration solutions (Docker, Kubernetes) for test environments and internal services
Support the integration of automated testing frameworks into CI/CD flows, ensuring test coverage and results are tracked and visible
Evaluate and introduce new DevOps tooling and methodologies to keep the team at the forefront of engineering efficiency
What We Need to See:
Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field
8+ years of hands-on experience in DevOps, platform engineering, or software infrastructure roles
Strong proficiency in CI/CD tools with hands-on experience in GitLab CI/CD pipelines; familiarity with Jenkins, GitHub Actions, or equivalent is a plus
Experience with containerization and orchestration — Docker, Kubernetes
Solid scripting and automation skills — Python, Bash, and/or similar
Familiarity with infrastructure-as-code tools (Terraform, Ansible, or similar)
Deep familiarity with Linux environments and system administration
Experience with version control systems (Git) and branching strategies
Strong debugging, problem-solving, and root-cause analysis skills
Ways to Stand Out from the Crowd:
Experience building and scaling DevOps infrastructure for hardware validation or embedded systems environments
Background working with test execution frameworks and integrating them into CI/CD pipelines
Experience with monitoring and observability tools (Prometheus, Grafana, ELK Stack, or similar)
Knowledge of cloud platforms (AWS, GCP, Azure) or on-premise HPC environments
Experience integrating AI/ML workflows and AI agent pipelines into CI/CD flows, including model versioning, automated testing, and deployment automation for AI-driven systems
NVIDIA has some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. We are 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.
Skills Required
- Bachelor's or Master's degree in Computer Science, Software Engineering, or related field
- 8+ years hands-on experience in DevOps, platform engineering, or software infrastructure roles
- Hands-on experience with GitLab CI/CD pipelines
- Familiarity with Jenkins, GitHub Actions, or equivalent CI/CD tools
- Experience with containerization and orchestration (Docker, Kubernetes)
- Scripting and automation skills (Python, Bash)
- Familiarity with infrastructure-as-code tools (Terraform, Ansible)
- Deep familiarity with Linux environments and system administration
- Experience with version control systems (Git) and branching strategies
- Strong debugging, problem-solving, and root-cause analysis skills
- Experience with monitoring and observability tools (Prometheus, Grafana, ELK Stack)
- Knowledge of cloud platforms (AWS, GCP, Azure) or on-premise HPC environments
- Experience building/scaling DevOps for hardware validation or embedded systems
- Experience integrating AI/ML workflows, model versioning, and automated testing into CI/CD
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
