About Me

B.S. Electrical & Computer Engineering, Carnegie Mellon University — Research Honors. 20+ years at the hardware-software boundary.

Liam D. Gray

I build at the intersection where hardware meets software — from device drivers shipping on hundreds of millions of devices to cryptographic evidence pipelines for autonomous agents. My career has spanned systems engineering at Qualcomm and Wabtec, computer vision, blockchain and zero-knowledge proofs, AI and LLM systems, and full-stack development.

Career Highlights

Qualcomm — Device Drivers & Embedded Systems

Developed device drivers, DMA engines, and real-time firmware for mobile platforms shipping at scale. Assembly-language debugging, RTOS integration, inter-processor communication, and hardware bring-up.

Wabtec — Real-Time Embedded Systems

Built and debugged real-time control systems for rail safety equipment. Interrupt-driven firmware, hardware-in-the-loop testing, and safety-critical software under regulatory compliance.

Carnegie Mellon University — B.S. Electrical & Computer Engineering

Graduated with Research Honors. Foundation in signals, systems, and information theory — how I learned to think about data integrity and evidence pipelines.

I started at the bottom of the stack — device drivers, DMA controllers, real-time operating systems, assembly language. That foundation in deterministic, resource-constrained systems shaped everything I do. When I later moved into computer vision, blockchain, AI, and data pipelines, I brought the same rigor: every cycle counts, every byte matters, and correctness isn't negotiable.

Over the years, I've built computer vision tracking systems from scratch, designed cryptographic decision protocols, written extraction pipelines that pull structured data from hostile environments, and created automation infrastructure that turns chaos into clean, auditable records. I've worked on zero-knowledge proofs and agent-native payment protocols — and also on the front lines of mundane-but-critical data entry and migration.

That range — from DMA engines to RAG pipelines, from assembly to cryptographic provenance — is the point. Most engineers live entirely on one side of the abstraction boundary. I work at the boundary itself.

The Bridge

I take academic research and implement it as production-grade systems code. If your ML team found a paper they can't implement, or your systems team can't keep up with AI advances — I sit at that intersection.

Today, I focus on remote consulting — helping teams bridge the gap between research and production. Fixed-price engagements, 1–3 month sprints, delivering working software rather than reports. Whether it's a performance-critical C++ patch, a computer vision pipeline, or an agent-native payment infrastructure, I bring the same systems-engineering rigor.

Technical Toolkit

C C++ Assembly Device Drivers DMA RTOS FPGA Verilog Python Rust Go TypeScript JavaScript Node.js React Computer Vision OpenCV AI / LLM RAG Pipelines Blockchain Zero-Knowledge Proofs Solidity PostgreSQL SQLite Cloudflare Workers Docker Linux Git CI/CD Shell Scripting REST APIs DSP

Let's Work Together

Remote consulting. Fixed-price engagements, 1–3 month sprints. Available for projects, technical advisory, and research-to-implementation work.

Get in Touch