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Developer Tools DevOps Engineer

Job in Coos Bay, Coos County, Oregon, 97458, USA
Listing for: NVIDIA
Full Time position
Listed on 2026-02-18
Job specializations:
  • Software Development
    DevOps, Software Engineer
Salary/Wage Range or Industry Benchmark: 276000 USD Yearly USD 276000.00 YEAR
Job Description & How to Apply Below

Employer Industry: Technology (Software Development)

Why consider this job opportunity
  • Salary range up to $276,000 for Level 4 positions
  • Eligibility for equity and comprehensive benefits
  • Opportunity to work with cutting‑edge technologies in a dynamic and innovative environment
  • Collaboration with talented professionals across various engineering teams
  • Chance to make a significant impact on product quality and delivery in a fast‑paced Dev Ops setting
What to Expect (Job Responsibilities)
  • Own and enhance CI/CD pipelines for multiple Developer Tools products, ensuring fast, reliable builds and automated testing
  • Streamline product delivery operations by tracking, measuring, and reporting critical metrics and regression testing
  • Collaborate with engineering and global infrastructure teams to improve product quality baselines and ensure rapid delivery
  • Document runbooks, standards, and guidelines to facilitate the adoption of modern Dev Ops patterns
What is Required (Qualifications)
  • Bachelor’s Degree in Systems/Software/Computer Engineering, Computer Science, or equivalent experience
  • Minimum of 5 years of experience in a large-scale software development environment as a Dev Ops, Site Reliability, or Build/Release Engineer
  • Proficiency in Python, Perl, and Bash/Shell scripting
  • Strong knowledge of Linux, networking, storage, and security
  • Experience with continuous integration systems (e.g., Jenkins, Git Lab, Gerrit)
How to Stand Out (Preferred Qualifications)
  • Proven experience running shared CI/CD platforms for multiple teams
  • Background in supporting developer tools, SDKs, or complex C/C++ software stacks
  • Hands‑on experience with GPU/HPC or AI/ML workloads, with an understanding of their unique CI/CD and infrastructure needs
  • Familiarity with containers and orchestration technologies (e.g., Docker, Kubernetes)

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