Hello, I'm Maruthi Sai Ganesh Reddy

Machine Learning Engineer & AI Developer

Building intelligent systems for a data-driven world.


View My Work

About Me

I am an experienced Machine Learning Engineer and AI Developer with a Master's in Computer Applications. I specialize in designing and deploying end-to-end AI solutions, from developing robust predictive models to turning raw data into actionable insights. My journey began with an impactful internship at AI Varient, where I honed my skills in supervised learning, recommendation systems, and NLP.

Building on that foundation, I now focus on developing scalable and production-ready machine learning pipelines. My technical expertise spans Python, TensorFlow, Scikit-learn, and NLP frameworks, and I'm adept at leveraging data to solve complex business problems. I am driven by a passion for continuous learning and collaboration, always seeking to create impactful solutions that bridge the gap between data and real-world applications.

Skills & Tech Stack

Languages

Python SQL R

ML Frameworks

Scikit-learn TensorFlow Keras PyTorch NLTK

Data Tools

Pandas Numpy Plotly Seaborn Tableau

Cloud & DevOps

Docker AWS GCP

Gen AI

Langchain Groq Cloud Prompt Engineering LLM's

Featured Projects

AI Study Assistant

EduBot – AI Study Assistant

EduBot – An AI-powered study assistant that uses RAG (LangChain + FAISS + HuggingFace + Groq LLMs) to answer questions directly from uploaded documents.

RAG, Groq LLMs, Prompting
View Project
Cold Email Generator

Cold Email Generator

A Streamlit app that leverages LangChain + Groq LLMs to extract resume/job details and generate personalized recruiter emails automatically.

Streamlit, LangChain, Groq (Gemma2-9b-it)
View Project
Recommendation System Project

Recommendation System

Developed a model using collaborative filtering to provide personalized recommendations, enhancing user engagement and sales.

Python, Scikit-learn, NLP
View Project

Experience

Machine Learning Engineer
(Current Role)

May 2025 - Present

  • Designing and developing end-to-end machine learning pipelines.
  • Deploying and monitoring models in production environments.
  • Collaborating with cross-functional teams to integrate AI solutions into products.

Data Science Intern
AI Varient

Nov 2024 - Mar 2025

  • Developed and evaluated supervised learning models (Regression, Classification) using scikit-learn and XGBoost.
  • Built customer churn prediction and recommendation system prototypes.
  • Applied Natural Language Processing (NLP) techniques for customer feedback analysis and sentiment classification.

Master of Computer Applications
JNTUK

2022 - 2024

Completed a Master of Computer Applications program, focusing on core concepts of data structures, algorithms, and software development, which laid the foundation for my career in AI.

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