Ehsan SadrFaridpour 🤖

Ehsan SadrFaridpour Ehsan Sadr-farid-pour

Senior Data Scientist | Enterprise GenAI & Production ML Systems

I build reliable production AI systems that connect machine learning and large language models with enterprise knowledge and real-world workflows.

RAG · LLM Evaluation · Retrieval · MLOps · Cloud AI · Observability

About

I’m a Senior Data Scientist at Moderna working on production AI and enterprise GenAI systems. My work spans RAG and retrieval architectures, LLM evaluation, knowledge governance, cloud-based ML services, production reliability, and forecasting platforms.

My background combines software and infrastructure engineering, machine learning research, and end-to-end production ML. I’m particularly interested in building reliable AI systems that connect models with enterprise knowledge and real-world workflows, with a focus on grounded retrieval, evaluation, observability, and scalable system design.

I hold a PhD in Biomedical Data Science and Informatics and an MS in Computer Science from Clemson University.

What I Build

Reliable AI systems designed for enterprise knowledge and real-world operations.

Enterprise GenAI & Knowledge Systems

Architect and productionize enterprise RAG systems with governed retrieval, source citations, metadata-aware search, document lifecycle controls, observability, and production reliability.

AI Evaluation & Retrieval Quality

Design evaluation systems that separate retrieval quality from answer-generation quality using gold and SME-reviewed datasets, retrieval metrics, citation coverage, evidence sufficiency, unsupported-answer behavior, and latency.

Production ML & Forecasting Platforms

Own and modernize production ML workflows with traceability, observability, AWS-managed execution, CI/CD, and repeatable operating practices that reduce manual operational work.

Experience

Selected recent roles; additional experience and education are available on the Experience page.

Moderna — Senior Data Scientist

2023–Present — Lead architecture and productionization of enterprise AI systems spanning GenAI/RAG, retrieval and evaluation, governed enterprise knowledge, cloud ML services, observability, and production reliability. I also own modernization and reliability work for production forecasting workflows and reusable ML operating patterns.

Infor — Senior Data Scientist

2021–2023 — Developed and productionized end-to-end machine learning solutions in AWS and helped turn applied ML concepts into deployable capabilities using repeatable MLOps practices.

Lowe’s — Data Scientist

2020–2021 — Built cloud-based machine learning applications and applied statistical modeling and demand forecasting to operational business problems.

Research Background & Publications

My research background is in scalable machine learning, NLP, large and imbalanced datasets, and biomedical data science. This work provides the algorithmic foundation for my current focus on reliable production AI systems.
Featured Publications
Recent Publications
(2019). Engineering Fast Multilevel Support Vector Machines. Machine Learning.
(2019). Predictive Models for Bariatric Surgery Risks with Imbalanced Medical Datasets. Annals of Operations Research.
(2017). Algebraic Multigrid Support Vector Machines. In ESSAN 2017.
Talks
Writing

Let’s Connect

I enjoy exchanging ideas on reliable GenAI, retrieval and evaluation, production ML, and scalable AI systems.