Senior DevOps and Infrastructure Engineer, Enterprise Systems

Sustainable Talent is partnering with Nvidia a global leader who's been transforming computer graphics, PC gaming, and accelerated computing for over 25 years. We are looking for a Senior DevOps and Infrastructure Engineer, Enterprise Systems to support our client's IPP's (Infrastructure, Planning and Process) Team.

This is a W-2 full-time contract based in Santa Clara, CA. We offer competitive pay $60-$70/hr based on factors like experience, education, location, etc. and provide full benefits, PTO, and amazing company culture!

IPP is a global organization within NVIDIA. This group works with various other groups within NVIDIA such as Graphics Processors, Mobile Processors, Deep Learning, Artificial Intelligence and Driverless Cars to cater to their infrastructure needs. These cloud services provide almost half a million automated jobs per day on thousands of servers helping with the productivity of thousands of software engineers worldwide. The cloud hosts a heterogeneous mix of machines and devices with various operating systems (Windows/Linux/Android), a multitude of hardware platforms both NVIDIA GPUs and Tegra Processors. Are you passionate about distributed infrastructure and looking for sophisticated, critical issues, ready to build the next generation of cloud services, design creative solutions, mine through data to uncover real problems and fix them?

What you'll be doing:

• Support Infrastructure Team Operations queue working within our Infrastructure and Cloud Operations Environments.

• Support DC and Cloud based Infrastructure system enrollments, deployments, troubleshooting and operations

• Assist in roll-out and deployment of new development features aimed at supporting the latest NVIDIA hardware and technologies.

• Work closely with world-class engineers, architects, technical product managers and application developers setting the best strategies in place for a product launch.

• Defining and implementing full scale solutions for product onboarding into our hosted and private cloud environments.

• Solve sophisticated problems involving multi-site deployments of NVIDIA products.

• Collaborate with multi-functional teams, including system engineering, software engineering, mechanical/thermal engineering, operations, data center teams, external vendors, and other partners to successfully deliver a reliable and robust platform from concept to prototype to deployments.

• Directly contribute to the overall quality of deployments and improve time to market next gen products.

What we need to see:

• Bachelor's or Master's Degree in Computer Science or Software Engineering, or equivalent experience.

• 5+ years of relevant experience.

• 3+ years of Linux and Scripting experience.

• Solid background on supporting private Cloud and HW operations

• A track record of quickly understanding new technologies outside of your domain expertise and deploying systems in sophisticated configurations from hardware through multiple layers of software in a fast-paced environment.

• Strong technical skills and understanding of embedded systems, orchestration & automation systems, data centers and cloud architecture, as well as excellent communication and planning skills.

• Strong problem-solving ability and experience in product engineering/failure analysis and debug/ HW or test design.

• Detailed understanding of HW system configurations, including BIOS, Compute, Storage and Networking.

Ways to stand out from the crowd:

• Experience in large scale QA environments, for product bring ups.

• Operations Support managing Bug Queues and Support Tickets.

• Background with supporting GPUs, embedded device development, driver development and CUDA applications.

• Experience with converged and hyper-converged hardware and servers.

• Background with Bash and Python.

• Familiarity with Jenkins, Ansible and REST APIs.

• Strong background on Windows & Linux administration.

Sustainable Talent is a M/F+, disabled, and veteran equal employment opportunity and affirmative action employer.