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# member of NVIDIA's Analytics and Data Intelligence Engineering Operations

- **Company:** NVIDIA Corporation
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Bash Shell, C++ (Programming Language), Ubuntu (Operating System), Cloud Computing, Nvidia CUDA, Computer Programming, Databases, Computer Engineering, Continuous Delivery, Continuous Integration, Extract Transform Load (ETL), Data Transformation, Data Visualization, DevOps, Github, Data Intelligence, Python (Programming Language), Linux System Administration, Machine Learning, Open Source Technology, Cloud Services, Server Administration, Software Engineering, Supercomputing, Scripting, Graphics Processing Unit (GPU), Sysadmin, Git, Build Management, Containerization, Information Technology, Build Process, Docker, Service Stack, Jenkins
- **Published:** September 5, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-engineer-build-and-devops-adi-charlotte-nc--80105080-de7a-4749-aac1-6d966c3c9b7a

## About the Role

* Bachelor of Science in Computer Engineering, Computer Science or related technical field or equivalent experience
 * 8+ years of technical experience primarily related to DevOps
 * Proven experience in programming and automation with scripting languages (Bash and Python preferred)
 * Experience with Conda and/or PyPI packaging, especially building and publishing
 * Experience with container technologies such as Docker, especially building and publishing
 * Detail-oriented and comfortable supporting and prioritizing amongst multiple teams
 * Experience with administration, optimization, and troubleshooting of CI/CD and related tools (including Jenkins, Git, GitHub Actions)
 * You have worked with cloud services (AWS, Azure, and others), especially permissions, budget, and cost management
 * Linux system administration experience (Ubuntu strongly preferred)

Ways to stand out from the crowd:

 * Background with NVIDIA's technology stack, including CUDA toolkit and drivers
 * Experience in software development, build, and/or related DevOps
 * Experience with GitHub operations, including user, repository, and organization management and permissions
 * Prior work with open-source development and community building on GitHub
 * Strong verbal and written communication skills, Amazon Web Services (AWS), Artificial Intelligence (AI), Automation, Bash Scripting, Best Practices, Budget Management, Build Management, C++ Programming Language, CUDA (Compute Unified Device Architecture), Cloud Computing, Communication Skills, Computer Engineering, Computer Science, Continuous Deployment/Delivery, Continuous Integration, Cost Control, Customer Support/Service, Data Science, Data Visualization, Database Extract Transform and Load (ETL), DevOps, Fortune 500 Customers, GPU (Graphics Processing Unit), Git, GitHub, Identify Issues, Jenkins, Legal, Linux Administration, Machine Learning, Microsoft Windows Azure, Multitasking, Open Source, Operational Support, Organizational Development/Management, Presentation/Verbal Skills, Purchasing/Procurement, Python Programming/Scripting Language, Science Library, Scripting (Scripting Languages), Software Administration, Software Development, Systems Administration/Management, Team Lead/Manager, Team Player, Ubuntu, Writing Skills

## Description

NVIDIA is widely considered to be one of the world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! We are looking for a hardworking member of NVIDIA's Analytics and Data Intelligence Engineering Operations team, supporting multiple engineering teams working on data science (and adjacent) libraries such as RAPIDS.

RAPIDS is the open-source suite for GPU-accelerated data science, spanning from ETL and data transformation to visualization, graph analytics, and machine learning. RAPIDS supports customers and partners ranging from individual data scientists to the world's largest supercomputers and Fortune 500 companies. As a DevOps Engineer, you'll have the opportunity to help support and grow the RAPIDS project. You will work closely with RAPIDS build and development teams to ensure high-quality releases of CUDA/C++ and Python libraries as well as containers.

What you'll be doing:

 * Work in a team of DevOps engineers supporting multiple software projects in the data science and AI domain, many of them open source
 * Manage cutting-edge hardware and help inform purchasing decisions for the team
 * Collaborate with build engineers, developers, and management to ensure the delivery of high-quality software
 * Develop and modernize packages, such as streamlined Python wheels, for RAPIDS data science libraries
 * Design and maintain container build processes
 * Take a hands-on approach working with engineers on the team to implement DevOps best practices
 * Execute on a range of DevOps initiatives including CI/CD, observability, security/legal compliance, and SysAdmin tasks
 * Operate and maintain our infrastructure and development processes


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