Lead Applied AI/ML Engineer (Solutions Architecture) @ Databricks | Author | Open Source Contributor
Building ML platforms at scale. Helping enterprises ship AI from prototype to production.
Packt Publishing, 2023 | 244 pages
End-to-end guide for building production ML systems on Databricks - from data engineering to MLOps. Reached best seller status in its category within 2 weeks of release.
Research Affiliate, Johns Hopkins University
Active contributor to MLflow (23K+ stars) - the leading open-source ML lifecycle platform.
Recent PRs:
- #19152 -
inference_paramssupport for LLM Judges (Approved) - #19237 - Phoenix & TruLens third-party scorer integrations
- #19238 - Async predict support for ChatModel/ChatAgent
- #19248 - Configurable parallelism for GenAI evaluation
- TechFutures 2025 (NYC) - End-to-End MLOps Pipelines Workshop (GitHub)
- Data Con LA 2022 - Simplifying AI/ML using Databricks Feature Store (YouTube)
- Data Con LA 2021 - Detecting Fake Reviews at Scale using Spark and John Snow Labs (YouTube)
- NYU Guest Lecture - ML Pipeline with Apache Spark



