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A Python library for inference-time scaling LLMs

I'm a Technical Product Manager at Red Hat AI, working with the AI Innovation Team to translate emerging research into practical product capabilities. My focus is bringing inference-time scaling, advanced model customization, and post-training techniques into enterprise AI platforms, helping organizations get more value from AI without starting from scratch.
Before Red Hat, I spent seven years at IBM Research, supporting AI research organizations and large-scale partnerships, including the MIT-IBM Watson AI Lab. I spent most of that time connecting research, product strategy, and customer needs to accelerate the path from ideas to real-world impact.
Outside of work I'm usually putting together side projects. I'm currently working on Reel Palate and a handful of other side projects. I studied at Auburn, where I worked in sports information and media relations, and I'm still a big sports fan (Auburn, Orioles, Chelsea, Timberwolves).
Auburn University
Sports Information & Media Relations
IBM Research
7 years · MIT-IBM Watson AI Lab
Red Hat AI
2025 · AI Innovation Team
Things I've built or am building.
A Python library for inference-time scaling LLMs
Build task models that replace frontier API calls
Synthetic Data Generation Toolkit for LLMs
An algorithm-focused interface for common llm training, continual learning, and reinforcement learning techniques
Domain-agnostic multi-agent software design and evolution harness
Forecasting benchmark
Inference-time scaling strategy
AI-powered work vault built on Obsidian + Claude Code
Red Hat AI Innovation Team website
What I've been working on lately.
Sports have been a part of my life since before I can remember.
Auburn Tigers
NCAA
Baltimore Orioles
MLB
Chelsea FC
Premier League
Minnesota Timberwolves
NBA
Tampa Bay Buccaneers
NFL
Movies & TV
Cooking
Video Games