AI Engineer · Retired Special Forces Medical Sergeant Building practical, high-reliability systems across applied AI, automation, and intelligence-driven workflows.

I engineer AI systems for the real world — the kind that have to work under load, on deadline, and in front of people who depend on the output.

My background is an unusual mix:

• Software & AI engineering — applied ML, LLM workflows, backend systems
• Military leadership — leading teams and owning outcomes under pressure
• Medical decision-making — high-stakes judgment in austere environments
• Product thinking — building for real operators, not just demos

Before moving full-time into AI and engineering, I served as a Special Forces Medical Sergeant. That experience still shapes how I build: reliability matters, clarity matters, and execution matters. Build clearly, move fast, stay grounded, and ship systems that are actually useful.

• 🤖 Agentic AI systems — multi-agent orchestration and tool use
• 🔁 LLM workflows & automation — turning models into reliable pipelines
• 🔎 Intelligence & research platforms — retrieval, synthesis, decision support
• 📊 Applied machine learning — from clinical risk to computer vision
• 🛠️ Data infrastructure & backends — the unglamorous parts that make it real

Languages

AI / Data

Backend / Infra

Exploring / Working With

 Retrieval systems · Multi-agent orchestration · Decision-support pipelines

Machine learning pipeline for early sepsis risk identification using structured clinical features — with full preprocessing, feature engineering, class-imbalance handling, hyperparameter optimization, and rigorous model evaluation.

Deep learning tool that converts images of handwritten mathematical expressions into LaTeX, built on a sequence-to-sequence architecture with a CNN/ResNet encoder.

Computer vision system for multi-class plant disease detection, using a CBAM (Convolutional Block Attention Module) augmented ResNet18 architecture.

Real-time collaborative parking optimization combining game-theory Nash equilibrium, A* pathfinding, ML forecasting, and driver-psychology modeling.

This GitHub is where I keep engineering projects, AI/ML experiments, prototypes, research-driven builds, and tooling for automation, intelligence, and decision support.

• 🌐 Portfolio: jeremycleland.com
• 💼 LinkedIn: jeremy-cleland
• 🏢 Cleland Co (my company): clelandco.com

I'm interested in building systems that are useful, resilient, and operationally real.