SUJITH CHOLLETI

Architecting intelligent solutions using GenAI, LLMs, and Multi-Agent Systems. Transforming raw data into actionable foresight.

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Profile Summary

AI/ML Engineer with 3+ years of hands-on experience in Data Analysis, Machine Learning, and Generative AI applications. Specialized in building end-to-end data solutions, integrating RESTful APIs, and automating workflows.

Currently focused on Large Language Models (LLMs), Agentic AI frameworks, and prompt engineering to drive business transformation.

M.P.S. Data Science (UMBC)
GPA: 3.93/4.0

Bridging Theory & Application

3+ Years

Experience

10+

Projects

3

Certifications

100%

Commitment

Core Domains

Generative AI Predictive Modeling Synthetic Data RAG Pipelines Agentic AI

Technical Arsenal

Languages & Core

Python 95%
SQL 90%
Java 75%

AI Frameworks

TensorFlow PyTorch LangChain LlamaIndex OpenAI Agents SDK FAISS

Cloud & Deployment

AWS (S3, EC2)
Azure
Docker
Jenkins
Databricks

Data & Visualization

Power BI
Tableau
Streamlit
Spark

Professional Trajectory

AI/ML Engineer

Caspex Corp (Experian)

May 2024 - Present

  • Deployed scalable Dockerized solutions on AWS EC2.
  • Engineered RAG-based pipelines using Pinecone & vector search.
  • Built multi-agent frameworks with OpenAI Agents SDK & LangChain.
  • Implemented MLflow tracing with Databricks for LLM monitoring.

AI Engineer

Secure Our Families

Jan 2024 - Dec 2024

  • Designed Al-driven solutions with LangChain & OpenAI APIs.
  • Built Power BI pipelines for real-time tracking.
  • Developed LLM-powered assistants for automation.

AI/ML Engineer

DXC Technology

May 2021 - Aug 2022

  • Developed ML models using Python, TensorFlow, and PyTorch.
  • Fine-tuned LLM/NLP pipelines for semantic search.
  • Benchmarked models (Accuracy, Precision, F1-score).

Key Deployments

Personal Chat Bot (RAG)

Developed an AI-powered chatbot using Streamlit, OpenAI GPT-3.5, and FAISS vector DB for interactive document querying.

Streamlit LangChain PyPDF2

Air BnB Price Prediction

Refined ML models (XGBoost, Random Forest) for pricing forecasts. Built interactive Streamlit app for real-time predictions.

XGBoost Python Regression

Taxi Payment Prediction

Analyzed large datasets with SQL. Achieved 99% accuracy using Random Forest and Decision Trees for payment behavior.

SQL Power BI Scikit-learn

Flight Delays Analysis

Performed EDA and built logistic regression models (93.7% accuracy) to forecast delays and reduce operational costs.

EDA Logistic Regression Visualization

Initiate Connection

Ready to collaborate on the next generation of AI solutions.

Email LinkedIn
443-858-6624