Jason M.

🚀 🥇 Expert-Vetted | Hands-On AI/ML Engineer | I Build LLM Apps, RAG Systems & AI Agents (MCP, LangGraph) | Python, AWS, GCP, Azure | Healthcare & FinTech

👁‍🗨 Overview

I build and ship production AI systems myself, end to end. No handoffs, no delegation: I design the architecture, write the code, and stay on it until it is deployed, monitored, and generating ROI. I bring 15+ years of hands-on AI/ML engineering, a PhD in Machine Learning from Iowa State University, and a Master's in Computational Neuroscience from UC San Diego.

✅ What I Build:
• LLM Applications: RAG pipelines, chatbots and copilots, document AI, semantic search, structured data extraction
• AI Agents: Multi-agent systems, MCP (Model Context Protocol) tool integrations, LangGraph orchestration, function/tool calling, agentic workflow automation
• Model Customization: Fine-tuning (LoRA/QLoRA, RLHF/DPO), prompt optimization, evals and guardrails, open-weight model serving (vLLM)
• Healthcare AI: Clinical trial automation, medical document generation, HIPAA-compliant systems
• Full-Stack AI Products: Python/FastAPI backends, React frontends, Kubernetes, CI/CD across AWS, GCP, Azure

🎯 Recent Hands-On Builds:
• Engineered a clinical trial intelligence system for enterprise pharma: ingested, embedded, and indexed 100K+ trials with multi-index, multi-LLM RAG and advanced PDF parsing, powering Q&A, chat, and benchmarking
• Built a GenAI product that drafts 100+ page regulatory clinical trial protocols (95% of the full M11 document), with multi-agent validation, consistency, and styling checks
• Coded and deployed an ICD-10 billing code prediction model on GCP and an EHR-integrated physician sidebar on AWS EKS
• Rescued a failing third-party ML platform, refactored it, and took it to production on AWS at ResMed (NYSE: RMD), enabling their first commercial AI healthcare product
• Built ML-powered ad targeting and recommendation systems generating $100K+/month, plus AI products earning $1M+ revenue in year one

💼 Industry Expertise:
• Healthcare/Pharma: Clinical trials, EHR API integration, medical AI, FDA-regulated software
• FinTech: Real-time fraud detection, card-linked platforms, transactional APIs (MasterCard and Visa partnerships)
• Enterprise SaaS and Retail/E-commerce: Multi-tenant APIs, recommendation engines, customer analytics

🔧 Technical Stack:
AI/ML: GPT-5, Claude, Gemini, Llama, DeepSeek, Qwen; fine-tuning (LoRA/QLoRA, PEFT, RLHF/DPO); RAG and GraphRAG, hybrid search, rerankers, embeddings Agents: MCP, LangGraph, LangChain, LlamaIndex, CrewAI, OpenAI Agents SDK, structured outputs, tool calling Languages: Python, TypeScript/JavaScript, SQL, Java, Go Frameworks: PyTorch, Hugging Face, FastAPI, React, TensorFlow, Scikit-learn Serving & MLOps: vLLM, Ollama, AWS (SageMaker, Lambda, ECS/EKS), GCP (Vertex AI), Azure AI Foundry, Kubernetes, Docker, MLflow, Weights & Biases Evals & Observability: LangSmith, Langfuse, RAGAS, guardrails, LLM cost optimization Databases: PostgreSQL/pgvector, Pinecone, Qdrant, Weaviate, ChromaDB, Elasticsearch, MongoDB, Redis