Open to opportunities

Sahith User

@sahithuser

Message

I build production AI systems for search, risk scoring, and forecasting.

United States

Message

What I'm looking for

I'm looking to build secure, scalable production AI solutions, especially LLM applications, RAG systems, predictive models, and MLOps platforms that solve meaningful business problems.

I've built production AI systems for Verizon, PNC Investments, Wipro, and Unichem Laboratories across network operations, fraud detection, digital lending, and pharmaceutical analytics.

At Verizon, I designed an enterprise RAG knowledge assistant for network operations, combining semantic search, keyword retrieval, metadata filtering, reranking, and LLM-generated troubleshooting guidance. The platform improved retrieval relevance by approximately 28%, reduced unsupported responses by approximately 22%, and cut troubleshooting-information search time by approximately 35%.

At PNC Investments, I productionized fraud-detection and client-risk models supported by batch and near-real-time data pipelines, FastAPI services, monitoring, and controlled model releases.

I've also developed lending risk models, document-intelligence workflows, demand forecasts, ETL pipelines, and business dashboards. I work across Python, cloud ML platforms, MLOps, deep learning, NLP, and Generative AI to turn business requirements into secure, scalable AI solutions.

Experience

Work history, roles, and key accomplishments

Current

AI & Machine Learning Engineer

Current

Verizon

Jul 2025 - Present (1 year 1 month)

Designed and developed an enterprise RAG platform for network operations, improving retrieval relevance by 28% and reducing unsupported responses by 22%. Built scalable ingestion pipelines and deployed FastAPI microservices with Docker, Kubernetes, and CI/CD.

Python Faiss Pinecone OpenAI Transformers RAG fastAPI Docker Kubernetes CI CD MLFlow

Machine Learning Engineer

PNC Investments

Nov 2024 - Jun 2025 (7 months)

Developed and productionized machine-learning models for real-time fraud detection and client risk scoring. Engineered batch and near-real-time data pipelines and deployed scalable FastAPI microservices with Docker, Kubernetes, and MLflow.

Python PySpark Apache Spark Airflow Azure Data Factory SQL PostgreSQL fastAPI Docker Kubernetes MLFlow CI CD

Data Scientist

Wipro

Sep 2023 - Jul 2024 (10 months)

Developed machine-learning models for loan-default prediction and credit-risk assessment. Built scalable ETL pipelines and an LLM-powered document intelligence workflow, and created Power BI and Tableau dashboards for stakeholders.

Python PySpark Apache Spark AWS Glue SQL scikit learn XGBoost LightGBM LLM RAG Power BI Tableau

Data Scientist

Unichem Laboratories

Mar 2022 - Aug 2023 (1 year 5 months)

Developed machine-learning and time-series forecasting models for pharmaceutical demand prediction. Built data pipelines and applied NLP and Transformer-based methods for document classification and information extraction.