Used Tools & Technologies
GenAIRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 7
Go @ 6
IaC @ 4
Terraform @ 4
Python @ 6
Leadership @ 4
AWS @ 4
Azure @ 4
Mathematics @ 4
Microservices @ 4
Data Analysis @ 4
Reporting @ 4
GPU @ 4
Generative AI @ 4
AI @ 4
Profiling @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA has been reinventing computer graphics, PC gaming, and accelerated computing for 30 years. Today, NVIDIA is tapping into the potential of AI to define the next era of computing where GPUs act as the brains of computers, generative AI, robots, and self-driving cars. NVIDIA seeks highly skilled engineers immersed in a diverse, supportive environment.
Responsibilities
- Lead initiatives to transform IT compute platform architecture and build new service offerings across on-premises and cloud environments.
- Define and implement metrics to measure the efficiency of compute platforms and services and drive improvements.
- Collect and review system data for capacity and planning, analyze capacity data, develop enterprise-wide system plans, and coordinate implementation with management.
- Develop and maintain tools for collecting, analyzing, and visualizing data for reporting, alerting, and monitoring.
- Collaborate with leadership, senior engineers, program managers, and product managers to develop IT products and services that meet customer needs.
Requirements
- Bachelor's degree in Engineering, Computer Science, Mathematics, or related field, or equivalent experience.
- 12+ years of proven experience in compute platform engineering with a focus on automation.
- Proven experience in designing and deploying virtualization architectures.
- In-depth knowledge of hardware technologies including SR-IOV, DPU, and GPU, with a track record of implementing these in virtualized and containerized environments.
- Experience evaluating application architectures and identifying opportunities for containerization to improve scalability, reliability, and efficiency.
- Strong analytical skills with the ability to define and track key performance metrics.
- Experience developing tools for data analysis and performance profiling; development experience with Terraform and configuration management tools.
- Proficiency in programming languages such as Go and/or Python.
- Experience running large environments consisting of bare metal, very large virtualized environments (tens of thousands of VMs), and cloud infrastructure.
Ways to Stand Out
- Deep understanding of other infrastructure components like Storage, DNS, LDAP, and Security Tools.
- Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Solid understanding of microservices architecture, infrastructure as code (IaC), and configuration management tools.
Benefits
- Base salary (location and experience dependent): 200,000 USD - 322,000 USD.
- Eligible for equity and additional benefits (see NVIDIA benefits page: https://www.nvidia.com/en-us/benefits/).
Other Information
- #LI-Hybrid (role is listed as hybrid).
- Applications for this job will be accepted at least until February 13, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and states non-discrimination across various protected characteristics.