The NVIDIA DGXC Data Services team is developing a cloud-native stack of software services and tools for managing data across hybrid and multi-cloud infrastructures. We are building the next-generation data and storage infrastructure to solve the most challenging problems, such as storage, access, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. You will craft software services to deliver functionality to NVIDIA's internal platforms and our external-facing cloud infrastructure.
What you will be doing:
Design and build software code and cloud services for Data Management, including providing a catalog, managing metadata and life cycle of datasets and checkpoints
Connect with other technical leaders across NVIDIA to ensure you are using existing technologies where possible and that we are collaborating appropriately with their systems.
Collaborate with the NVIDIA research team to utilize new storage and compute innovations, including GPU direct storage and DPU.
What we need to see:
BS in Computer Science, Information Systems, or Computer Engineering (or equivalent experience) with 5+ years of proven experience
Strong foundation in algorithms and data structures and their real-world use cases.
Experience building and shipping services around Kubernetes, Cloud Native, and Cloud Service Providers. Experience with one of the leading cloud providers: AWS, GCP, or Azure.
Experience collaborating with teams to write software to support cloud services.
Background with backend systems and software engineering. Programming experience in a relevant language, e.g., Go, Python, C/C++, Java.
Understanding of standard approaches to software engineering, software architecture, and design. Ability to document software and services. Break down projects into practical tasks.
Communicate design, status, and other sophisticated subjects in written, visual, and oral formats. Ability and passion for working across teams and with collaborators on all sides of the project
Ways to stand out from the crowd:
Hands-on experience in building and managing large-scale data services.
Experience building products and services to solve enterprise-grade customer data analytics problems.
Experience with Apache Spark, Object Storage, Metadata Management, Data lake tools (Apache Iceberg), Machine Learning infrastructure toolset (Feature Stores). Computer science background with Distributed Systems as a specialization
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention, the GPU, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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
- BS in Computer Science, Information Systems, or Computer Engineering (or equivalent experience) with 5+ years of proven experience
- Strong foundation in algorithms and data structures and their real-world use cases
- Experience building and shipping services around Kubernetes, Cloud Native platforms, and Cloud Service Providers
- Experience with one of the leading cloud providers: AWS, GCP, or Azure
- Experience collaborating with teams to write software to support cloud services
- Background with backend systems and software engineering
- Programming experience in relevant languages (Go, Python, C/C++, Java)
- Understanding of software engineering best practices, software architecture, design, documentation, and task decomposition
- Ability to communicate design, status, and technical subjects in written, visual, and oral formats; cross-team collaboration
- Hands-on experience building and managing large-scale data services
- Experience with Apache Spark, Object Storage, Metadata Management, Apache Iceberg, Feature Stores, or ML infrastructure toolsets
- Specialization or experience in Distributed Systems
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.”
