David Katz

About

Hi, I'm David Katz, a Machine Learning Engineer focused on ML systems, model evaluation, ML platforms, MLOps, model serving, and inference. My background includes 5+ years of overall engineering experience across software, cloud infrastructure, enterprise AI, and edge deployment. I'm completing an M.S. in Computer Science at UT Austin, expected December 2026. My thesis evaluates compact language-model controllers for simulated X-ray peak centering using PyTorch, Hugging Face Transformers, PEFT/LoRA, supervised fine-tuning (SFT), reinforcement fine-tuning (RFT), and controlled evaluation against numerical baselines. This work was selected for a first-author poster and lightning talk at TACCSTER 2026. Alongside my thesis, I work part-time with Dell Medical School's NPRQI initiative on clinical-data mapping and SQL/OMOP analytical logic, translating pediatric emergency-care requirements into code and data definitions. My professional experience includes designing and building a RAGAS faithfulness-evaluation harness at CIBC, building computer-vision inference and deployment services shipped across 500+ NVIDIA Jetson Orin Nano devices at Spectral Tech AI, and demonstrating a data-govern

Experience

Education