We are seeking a highly skilled Data Platform SW Engineer to join the Applied Networking AI group. In this role you will help develop advanced data acquisition solutions for the fields of predictive-maintenance, root-cause analysis and AIOPS. You'll collaborate closely with subject-matter-experts (SMEs), applied-researchers, architects, data-engineers and other stakeholders to push the envelope forward in using cutting-edge technologies and data-driven insights to improve NVIDIA's products.
As a key contributor you will develop and own metric-extraction, measurement and telemetry tools that enable a high resolution viewpoint into the hardware. You will experiment and iterate fast and in collaboration with applied-researchers to improve our ML diagnostic and prediction toolkit.
What you'll be doing:
Lead the development of advanced metric and measurement tools for real-time data collection and processing, to enable a high resolution viewpoint into the full set of HW components that compose NVIDIA's AI factory solutions (GPUs, networking interfaces, etc).
Work alongside applied-researchers to experiment and iterate on the bridge between metrics and ML.
Partner with architects and product managers to gain a deep understanding of NVIDIA’s hardware and roadmap.
Collaborate with data-engineers to enable high resolution tools at scale.
What we need to see:
BSc in Computer Science, Electrical Engineering, Computer Engineering, or equivalent practical experience.
5+ years of hands-on experience demonstrating deep system knowledge and metric extraction development.
Strong understanding of networking, hardware/software systems, performance behavior, or failure analysis.
Solid understanding of AI/ML modeling and statistics.
Excellent ability to convey and communicate data-based insights to stakeholders and management.
Ways to stand out from the crowd:
Experience diagnosing or debugging modern AI hardware.
High energy and a positive, proactive and curious approach.
We are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Skills Required
- BSc in Computer Science, Electrical Engineering, Computer Engineering, or equivalent practical experience
- 5+ years hands-on experience with deep system knowledge and metric extraction development
- Strong understanding of networking, hardware/software systems, performance behavior, or failure analysis
- Solid understanding of AI/ML modeling and statistics
- Excellent ability to convey and communicate data-based insights to stakeholders and management
- Experience diagnosing or debugging modern AI hardware
- High energy and a positive, proactive and curious approach
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.”
