Open to opportunities

Shean Iban

@sheaniban

Message

Senior AI/ML engineer building production RAG, LLM, and real-time analytics that drive measurable business impact.

United States

Message

What I'm looking for

I’m looking to own production AI/ML and LLM systems end-to-end—RAG and agentic workflows, scalable data pipelines, and reliable MLOps (monitoring, retraining, CI/CD)—in cross-functional teams that value measurable business impact.

I’m a Senior AI/ML Engineer and Data Scientist with 8+ years designing, deploying, and optimizing production-grade AI/ML and LLM systems.

My expertise spans RAG pipelines, embeddings, vector search, predictive modeling, and real-time analytics—delivered across healthcare, fintech, SaaS, and enterprise environments with measurable outcomes.

I’ve reduced fraudulent transactions by 22%, improved healthcare patient readmission accuracy by 17%, and increased fan engagement by 20% through predictive modeling and recommendation engines.

I take end-to-end ownership of production ML pipelines—CI/CD, inference optimization, automated retraining, drift detection, and monitoring—while mentoring teams to standardize best practices. I build robust workflows using modern MLOps and data engineering platforms to keep models reliable and scalable.

Experience

Work history, roles, and key accomplishments

Current

Senior AI/ML Engineer

Current

Hexaware

Jan 2020 - Present (6 years 5 months)

Designed and deployed real-time fraud detection models reducing fraudulent transactions by 22% by integrating XGBoost, LightGBM, and PyTorch. Built production-grade RAG and agentic AI pipelines, optimized inference and cloud compute costs on AWS/Databricks, and implemented MLflow-based CI/CD with automated retraining and monitoring.

Real Time Fraud Agentic AI XGBoost LightGBM PyTorch AWS Databricks MLFlow

ML Engineer

Osprey

Mar 2017 - Dec 2019 (2 years 9 months)

Designed and deployed predictive healthcare models for patient readmission using TensorFlow and PyTorch, improving accuracy by 17%. Built ETL and analytics pipelines with PySpark and Airflow, developed RAG pipelines and AI agents using embeddings/vector search, and partnered with clinical and engineering teams to integrate models into operational workflows.

predictive modeling TensorFlow PyTorch Pyspark Airflow ETL Embeddings Model Validation

Software Engineer

DigitalOcean

Jan 2016 - Feb 2017 (1 year 1 month)

Developed web-based applications and internal tools for early-stage product MVPs. Built data ingestion and ETL pipelines with Python and SQL and implemented analytics dashboards with Tableau to deliver business insights.

Python SQL Web Application Development ETL Data Ingestion Tableau Dashboards