Open to opportunities

Shaik Gouse Mohiddeen

@shaikgousemohiddeen

Message

AI/ML Engineer with 4+ years building scalable ML and GenerativeAI solutions across healthcare and finance.

United States

Message

What I'm looking for

I’m looking to build production-ready LLM and ML systems—owning data pipelines, RAG, and real-time APIs in collaborative Agile teams, with strong MLOps and cloud engineering opportunities.

I’m an AI/ML Engineer with 4+ years building scalable machine learning and GenerativeAI solutions across retail, healthcare, and financial domains. I focus on LLM-powered applications, RAG pipelines, and real-time ML systems that deliver measurable impact.

In my recent work, I designed and deployed end-to-end ML pipelines for patient risk prediction, improving model accuracy by 20% and enabling early intervention strategies. I built RAG-based LLM pipelines using LangChain and Hugging Face, implemented semantic search with vector embeddings (FAISS) to reduce retrieval time by 40%, and evaluated LLM performance with automated metrics plus human-in-the-loop validation.

I also deliver production-ready systems through strong MLOps practices—MLflow for tracking and monitoring, AWS for scalable deployment (S3/EC2/Lambda/SageMaker), and containerized releases with Docker and Kubernetes plus CI/CD using GitHub Actions. I enjoy building and operating real-time inference APIs (FastAPI/Flask) and collaborating in Agile environments to ship reliable, data-driven outcomes.

Experience

Work history, roles, and key accomplishments

Current

AI/ML Engineer

Current

Baxter International

Mar 2025 - Present (1 year 3 months)

Designed and deployed end-to-end ML pipelines for patient risk prediction, improving model accuracy by 20% and enabling earlier clinical intervention. Built RAG-based LLM pipelines with LangChain/Hugging Face and reduced information retrieval time by 40%, while delivering real-time FastAPI inference APIs and AWS deployments.

Python LLMs (LangChain RAG Faiss fastAPI AWS Sagemaker MLFlow Docker Kubernetes

AI/ML Engineer

Ace Hardware

Jul 2024 - Feb 2025 (7 months)

Developed customer churn prediction models (XGBoost, Random Forest), reducing churn by 20%. Built GenAI/RAG-based product search and recommendation experiences, and engineered PySpark/Airflow ETL pipelines that reduced processing time by 40%, with real-time FastAPI inference for production deployment.

XGBoost Random Forest RAG Hugging Face SpaCy Prompt Engineering fastAPI Pyspark Airflow MLFlow

AI/ML Engineer

Cipla

Jan 2021 - May 2022 (1 year 4 months)

Built patient readmission prediction models, improving early detection rates by 22%, and developed NLP and RAG pipelines for clinical document retrieval. Implemented secure Flask APIs for model deployment and used SHAP/LIME for healthcare model explainability, processing 10M+ records via automated ETL workflows.

SpaCy Hugging Face RAG Flask AWS EC2 SHAP LIME ETL NLP

Data Scientist

Hdfc Bank

Jan 2020 - Jan 2021 (1 year)

Analyzed customer behavior and clickstream data using Python and SQL, and built customer segmentation models (KMeans, Decision Trees) to support targeted campaigns. Automated reporting to save 15+ hours/week and ran A/B tests to optimize marketing strategies based on measurable lift.

Python SQL Decision Trees A B Testing Click Stream Data Data Analysis K Means