Full-Time
Senior GPU Verification Architect
Posted on 1/24/2026
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
Compensation Overview
$184k - $356.5k/yr
Company Historically Provides H1B Sponsorship
Santa Clara, CA, USA
In Person
 Hardware Engineering (2) |
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- Completed a MS, PhD or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field with 7+ years of experience in related areas
- Background in Computer Architecture with experience in modeling
- Proficiency in C++, Python and ML frameworks like PyTorch, TensorFlow, Hugging Face Transformers, and LangChain
- Hands-on experience with LLMs (e.g. GPT, Claude, Llama) and multimodal models
- Strong collaboration skills with design and engineering teams
- Strong problem-solving and debugging skills, with a track record of driving issues to closure
- Develop and verify GPU/ SOC architectures while integrating GenAI applications to enhance overall productivity and streamline workflows
- Define, build, and drive the verification test plan for specific GPU products to ensure outstanding performance
- Ensure reliable execution of the defined test plan, triage failures, and successfully implement fixes to drive bugs to closure
- Guide the improvement of the simulation platform and expand other resources to support future GPU/ SOC architectures
- Build and evaluate prototypes using LLMs and multimodal models
- Develop and deploy scalable GenAI applications that integrate with existing workflows and enhance overall productivity
- Build full-stack applications and ML ops pipelines that embed GenAI into architectural workflows
- Ensure compliance with data privacy, IP protection, and design standards
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
Simplify's Take
What believers are saying
- Agentic AI adoption at scale drives major inflection in inference demand globally.
- Jensen Huang projects $3T-$4T global AI factory buildout through 2030.
- Data centre networking revenue surged 263% YoY to $10.98B in Q4 FY2026.
What critics are saying
- Nemotron 3 open weights enable AMD and Intel to replicate NVIDIA's software moat.
- Insider selling over three months signals executive doubt about sustaining 73% growth.
- $30B OpenAI investment exposes NVIDIA to catastrophic losses from governance collapse.
What makes NVIDIA unique
- Vera Rubin launching July 2026 reduces inference token costs tenfold versus Blackwell.
- Nemotron 3 Nano Omni achieves 9x higher throughput on consumer hardware like RTX 4090.
- Clear datacenter product roadmap extends through 2028 with Feynman arriving in 2028.
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6 month growth
↓ -1%1 year growth
↓ -3%2 year growth
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