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Sai Manish Goud

@saimanishgoud

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AI Engineer building local RAG assistants and MRI tumor classifiers with Python, PyTorch, LangChain, and ChromaDB.

India

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What I'm looking for

I’m seeking an AI Engineer or Machine Learning Engineer role where I can build and ship production-grade AI features spanning retrieval, prompting, and applied machine learning.

I built a local Retrieval-Augmented Generation assistant using Llama 3.2, Ollama, LangChain, and ChromaDB. It answers questions about PDFs offline, with a Streamlit interface and retrieval designed to reduce redundant context.

For my brain tumor classification project, I developed a PyTorch CNN to classify MRI scans into four tumor categories, achieving 92% accuracy. I presented the research at the 4th IEEE International Conference on Inventive Computing and Informatics (ICICI 2026).

I’ve also built a SQL analytics database for customer segmentation and revenue-trend analysis, and a machine learning pipeline to predict mutual fund returns. I’m seeking an AI Engineer or Machine Learning Engineer role building and shipping production-grade AI features across retrieval, prompting, and applied machine learning.

Experience

Work history, roles, and key accomplishments

Brain Tumor Classification using MRI Scans

Applied AI/ML Projects

Developed a CNN-based deep learning model in PyTorch to classify MRI brain scans into four tumor categories, achieving 92% accuracy. Presented research at IEEE ICICI 2026.

Python PyTorch OpenCV NumPy Matplotlib CNN Deep Learning

RAG-based AI Assistant

Applied AI/ML Projects

Built a fully local RAG assistant using Llama 3.2, LangChain, and ChromaDB for offline PDF question-answering. Engineered document chunking and embedding pipeline and implemented MMR retrieval with a Streamlit UI.

Python Ollama Lang Chain ChromaDB Nomic Embed Text Streamlit RAG MMR

Predicting Mutual Fund Returns

Applied AI/ML Projects

Built a regression-based machine learning pipeline to predict mutual fund returns from historical NAV data. Benchmarked Linear Regression, Random Forest, and XGBoost models using RMSE, MAE, and R².

Python scikit learn XGBoost Pandas Matplotlib regression Feature Engineering

E-Commerce Sales Analytics

Applied AI/ML Projects

Designed and normalized a relational database schema across 8 tables and wrote advanced SQL queries for customer segmentation and revenue-trend analysis. Automated operations with stored procedures, triggers, and indexing.

MySQL SQL Git Database Design Window Functions CTEs