Full-Time
Senior Formal Verification Engineer
Posted on 12/13/2025
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
Compensation Overview
$136k - $212.8k/yr
Company Historically Provides H1B Sponsorship
Santa Clara, CA, USA + 1 more
More locations: United States
Hybrid
 Hardware Engineering (2) |
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- BS/MS/PhD or equivalent experience in Computer Science, Computer Engineering, Electrical Engineering, or Mathematics.
- Five or more years of formal verification of GPU or CPU designs.
- Solid understanding of GPU and CPU architectures and designs.
- Ability to implement abstraction techniques for effective verification.
- Strong proficiency in agentic Large Language Model libraries/technologies such as LangChain, LangGraph, AutoGen, CrewAI, Retrieval-Augmented Generation, vector databases, prompt engineering, and knowledge graphs.
- Strong analytical skills to solve complex problems.
- Knowledge of formal verification methodologies and techniques.
- Hands-on experience with Verilog and SystemVerilog hardware description languages, temporal logic assertions, and the ability to understand complex register-transfer level designs quickly.
- Preferable experience with formal verification tools such as Jasper, VC Formal.
- Excellent interpersonal skills and ability to collaborate effectively with a distributed team.
- Identify key behaviors for verification to write clear test plans for complex designs.
- Implement test plans using the latest formal techniques, including development of environment assumptions, assertions and cover properties.
- Develop abstraction models to overcome complexity challenges and obtain full proofs, or bounded proofs with sufficient coverage.
- Develop AI agents which can process large codebase and waves failures to help in coding and debugging tasks.
- Collaborate with FV engineering teams to understand their specific needs and challenges and ensure our agent platform is well-suited to these needs.
- Develop and optimize retrieval and generation algorithms for enterprise data (text, code, and images) to build advanced AI applications.
- Integrate AI-driven optimizations into existing formal tools and flows.
- Articulate formal verification coverage of the design to partners.
- Lead with purpose and maintain high-quality engineering practices that inspire others to achieve excellence.
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
- Data centers generate 89% of $215.9B FY2026 revenue.
- $40B acquisitions like OpenAI bolster AI infrastructure dominance.
- Nemotron models and Drive Thor accelerate agentic AI adoption.
What critics are saying
- AMD MI450X outperforms Blackwell by 25% per watt in inference.
- Huawei Ascend 910D blocks $10B China AI sales due to bans.
- Google TPU v6 cuts hyperscaler GPU dependency by 60%.
What makes NVIDIA unique
- NVIDIA invented GPU in 1999, pioneering accelerated computing.
- CUDA platform from 2006 enables GPUs for AI and HPC.
- Holds 92% discrete GPU market share as of Q1 2025.
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6 month growth
↓ -1%1 year growth
↓ -3%2 year growth
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