Full-Time
Senior Performance Verification Engineer
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
Compensation Overview
$136k - $264.5k/yr
Company Historically Provides H1B Sponsorship
Santa Clara, CA, USA
In Person
On-site in Santa Clara, California.
Bachelor's, Master's, PhD
 Hardware Engineering (1) |
|---|
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- BS or MS in EE/ECE or equivalent experience. PhD is a plus
- 3+ years of experience in CPU performance modeling, performance correlation, performance analysis, or relevant experiences
- Strong understanding in CPU micro architecture and designs
- Experience with workload analysis and characterization
- Strong coding skills in scripting languages like Perl, Python, or C++
- Good communication skills and ability & desire to work as a team player are a must
- Technical leadership role to define/plan/implement/execute performance verification strategy of sophisticated CPU designs
- Ability to delve into lowest level details of CPU unit design specification, implementation and it's performance impact
- Interactions with architect and design engineers to define detailed scope of micro architectural features
- Draft detailed performance testplans and define/Create scalable micros to validate features
- Analysis and correlation of CPU benchmarks/workloads
- Build infra/tooling needed for efficient performance correlation debug
- Ability to lead and provide detailed technical guidance to junior engineers
- Agility to work on multiple tasks/projects
- Experience leading performance validation of major blocks of CPU pipeline
- Background with ARM A64, X86 Architectures
NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.
Company Size
10,001+
Company Stage
IPO
Headquarters
Santa Clara, California
Founded
1993
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Simplify's Take
What believers are saying
- NVIDIA reported $215.9 billion fiscal 2026 revenue, up 65%, on February 25, 2026.
- The August 10, 2026 Wall Street financing pact opens more buyers for NVIDIA hardware.
- Nemotron 3.5 Lightning boosts ecosystem lock-in while driving cheap GPU demand.
What critics are saying
- US Commerce tightened China chip controls again on May 31, 2026.
- The $500 billion financing push ties growth to GPU resale values and customer defaults.
- An AI hardware glut from AMD, Huawei, or Chinese foundries crushes collateral and pricing.
What makes NVIDIA unique
- CUDA remains the default software moat for AI training and deployment.
- NVIDIA secured SK Hynix as its largest memory partner in June 2026.
- Vera Rubin and Blackwell keep NVIDIA ahead in rack-scale AI systems.
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Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↓ -2%2 year growth
↓ -3%Nvidia has partnered with six US asset managers willing to raise $500 billion to finance AI infrastructure development. The chip giant is positioning AI infrastructure as a new asset class, with the plan hinging on GPUs retaining value over time like traditional hard assets rather than depreciating electronics. The approach carries risks. Ben Emons of FedWatch Advisors warned that Chinese manufacturers could flood markets with low-cost chips, potentially causing hardware prices to collapse and eroding collateral backing billions in private loans. Nvidia also launched Nemotron 3.5 Lightning, its first open-source AI model since CEO Jensen Huang advocated for open models. The lightweight model runs on a single GPU, potentially boosting chip sales by offering cheaper alternatives to proprietary models. Meanwhile, oil prices rose over 6% this week as prospects dimmed for a deal to increase traffic through the Strait of Hormuz.
Elon Musk has announced plans to scale SpaceX data centres from 1.4 gigawatts to 10 gigawatts by 2027, working exclusively with NVIDIA hardware. Research firm SemiAnalysis estimates this could generate $150 billion to $500 billion in capital spending. The move could push NVIDIA shares towards $500, building on its $5.42 trillion market capitalisation and 92% data centre revenue share. NVIDIA recently announced a $500 billion financing partnership with Apollo, BlackRock, and other major firms to support AI infrastructure buildouts. However, the proposal creates significant concentration risk. SpaceX would propose capital expenditure rivalling Amazon Web Services and Google combined, whilst being far less profitable. NVIDIA already holds $119 billion in supply commitments. If SpaceX funding tightens or hyperscale customers slow orders, the stock could face substantial downside risk. Meanwhile, AMD has surged 121% year-to-date versus NVIDIA's 17% gain.
AI infrastructure startup Trajectory has raised $40 million at a $300 million post-money valuation, led by Sequoia Capital with participation from Nvidia and Bessemer, according to The Information. The funding comes just two months after the company secured a $15 million seed round at a $115 million valuation. Founded in May by former Google DeepMind researchers Ronak Malde and Michael Elabd, alongside ex-Apple researcher Arjun Karanam, Trajectory focuses on continuous learning technology. The platform transforms user corrections, retries and edits into training signals, enabling AI models to improve after deployment. The company automates this process, allowing enterprises to continuously adjust models, prompts and harnesses based on real usage data. Clay, Decagon and Harvey are currently using or testing the technology.
Nvidia is developing Nemotron 4, a new AI model family aimed at rivaling top open-source models globally, The Information reported. The largest model is expected to have at least 1 trillion parameters, according to employees working on the project. Nvidia has not set a release date, though the model could be ready as early as late autumn. The company has yet to complete final training. Separately, Nvidia unveiled Nemotron 3.5 Lightning for tasks including code review and security monitoring. It also released NeMo Switchyard, an open-source model-routing library. The chip giant is among few major US firms releasing open-source models, which have gained attention as AI costs rise and Chinese models approach capabilities of systems from Anthropic and OpenAI.
Nvidia has released Nemotron 3.5 Lightning, its first open-source AI model since CEO Jensen Huang entered the open-source AI debate. The model was developed particularly for autonomous AI agents and will be available on HuggingFace and Nvidia's website. Huang previously argued that open-weight models allow companies greater control, spur competition, and bring down pricing. For Nvidia, open-source AI boosts chip sales, as the models still require GPUs to run. Companies including CodeRabbit and Harvey have tested the model. Nvidia also released NeMo Switchyard software to determine the most appropriate and cost-effective AI model for specific tasks. Nvidia used distillation techniques to give Nemotron 3.5 Lightning capabilities similar to its larger models.