Jon Wolfe

About Jon Wolfe

As an engineer and perpetual innovator, it is my goal to discover, explore, and solve problems from every angle. I work at the intersection of computer science, statistics, and machine learning—combining bold ideas with precise engineering to overcome obstacles as they emerge.I tend to seek out the largest, most grueling challenges available, both inside and outside of work. It could be an issue with DevOps innovation or testing, or the need to overhaul scheduling theory for memory-constrained devices. Or it might involve debugging electrostatic interactions of Styrofoam cups at the coffee bar, some problems being more urgent than others. In each situation, I dive in deeply, seek out partners from multidisciplinary teams (specifically for workplace challenges), and determine what the ideal outcome would be. With “perfection” as a target, I architect a solution and plan implementation to meet real-world demands and timetables.As the project progresses, I quickly and strategically confront every problem that arises. Big and small. Virtual or physical. I interview members of nearby groups to understand their workflows, and improve processes accordingly. I introduce automation. I integrate seemingly unrelated ideas, topics, and fixes to create a solution that works—even if it defies old ways of thinking and seeing and doing.I’m an engineer and technologist by nature, but also a collaborator, team builder, and lifelong learner. I love finding and solving problems, and living at the edge of what’s possible.My background includes: • 15+ years as engineer and architect for Qualcomm, Samsung, and other companies working with digital signal processors, microprocessors, and related hardware and software.• Training in Deep Learning (AI and Neural Networking), BS in Computer Engineering, JD in Law (I tested out a different path while working as an engineering contractor).Languages, tools, and a few skills:• Python, C, C++, Perl, Verilog, SystemVerilog • Linux, Jenkins, Jira, GitHub, ClearCase, MySQL, CoreMark, Raven, Bugzilla, and others • Computer Science & Engineering, Machine Learning, Mathematics, Statistics, Random Testing, Formal Verification, Collaboration, Communication, Problem Solving

Experience

1. Senior Asic Front End Infrastructure Engineer

   NVIDIA

   Dec 2025 — Present · Austin, TX, US

Education

• DeepLearning.AI (via Coursera)

  Deep Learning Specialization, AI and Neural Networking

• The University of Texas at Austin

  BS, Computer Engineering

• The University of Alabama School of Law

  JD, Emphasis in Intellectual Property (IP) and Business Law

Skills

• Digital Signal Processors
• Soc
• Asic
• Systemverilog
• Formal Verification
• Microprocessors
• Semiconductors
• Eda
• Computer Architecture
• Functional Verification
• Testing
• Open Verification Methodology
• Hardware