About Me!

Hello, I'm Venkatesh! - an AI/ML Engineer with 2 years of experience in building scalable, production-ready machine learning solutions.
My focus is on developing efficient, reliable, and deployable AI solutions that bridge the gap between research and real-world applications.
I enjoy working across the full lifecycle of AI/ML development — from data processing and model training to deployment and scaling in cloud environments. Passionate about deep learning, natural language processing, and applied AI.

What I Know:

• Electrical & Electronics – With a strong academic foundation in Electrical & Electronics Engineering, I built expertise in core engineering principles that shaped my problem-solving and system design skills.

• AI/ML Development – Experienced in end-to-end model development, fine-tuning, and deployment of scalable machine learning systems.

• Production Systems – Skilled in building cloud-ready, production-grade applications and pipelines ensuring reliability and scalability.

• Voice & Vision AI – Developed real-time systems for ASR, TTS, emotion detection, and facial recognition, enabling multimodal AI solutions.

• Backend Engineering – Proficient in API development, task orchestration, and scalable service design using FastAPI, Docker, Celery, and Redis.

• Agentic RAG – Specialized in context-aware LLM orchestration, query rephrasing, and intelligent agentic retrieval workflows.

• Document & Data Processing – Experienced in OCR, text & table extraction, semantic chunking, and vector database integration for knowledge-driven applications.

• Cloud & MLOps – Hands-on with AWS and Linux servers, containerization, and CI/CD for continuous training, testing, monitoring, and deployment.

• Application Development – Built and deployed Android applications integrating real-time AI/ML backends.

Education:

• 2019-2023

  • Easwari Engineering College
  • Anna University - Bachelor of Engineering
  • Electrical & Electronics Engineering
  • CGPA: 8.88

• 2017-2019

  • Holy Prince Mat Hr Sec School
  • State Board - Higher Secondary
  • Percentage: 76.1%

• 2012-2017

  • Kumara Raja Muthaiah Hr Sec School
  • State Board - SSLC
  • Percentage: 81.8%

Projects:

ITEL foundation:

AUG 2025 ∙ Finetuning GPT-2 Supervised Fine-tuned GPT-2 Medium for query rephrasing and context-aware responses, integrated into a Retrieval-Augmented Generation (RAG) workflow.

JUL 2025 ∙ Document Ingestion Pipeline Built an end-to-end pipeline with OCR, text & table extraction, semantic chunking, and vector DB integration, powered by Celery & Redis for scalable document processing.

NOV 2024 ∙ Puchho Agentic RAG Framework Developed a framework for multi-file retrieval, intent classification, and summarization with history-aware query rephrasing, including a voice-enabled Android interface.

NOV 2024 ∙ Bolo Real-time Voice Communication App Architected a real-time ASR → MT → TTS system enabling multilingual communication across 12 Indian languages, deployed in a native Android app.

CEET IIT Madras:

APR 2024 ∙ Emotion Detection for Meetings Designed a multimodal AI system combining facial emotion recognition and speech sentiment analysis to deliver real-time emotional insights in virtual meetings.

NOV 2023 ∙ Face Recognition Attendance System Built a Dockerized on-device facial recognition solution for 80+ employees with real-time logging via MySQL and microcontroller-based camera integration.

SEP 2023 ∙ Indian Sign Language Detection Created a prototype using MediaPipe for real-time ISL recognition and interactive visualization via Streamlit.

Course Works:

JAN 2025 ∙ DA6401 Introduction to Deep Learning – A deep learning module covering core concepts and hands-on implementation.

• Implemented a feedforward neural network with various optimizers and W&B tracking on MNIST using NumPy.
• Trained and fine-tuned CNNs for 10-class image classification using the iNaturalist 12K dataset.
• Built a seq2seq transliteration model for English-to-Tamil using GRU/LSTM with attention on the Dakshina dataset.

AUG 2024 ∙ EE5180 Introduction to Machine Learning – Applied foundational ML techniques to real-world datasets.

• Built regression models to predict song energy and classify danceability using linear and logistic regression.
• Implemented Perceptron and MLP models for both linearly and non-linearly separable datasets.
• Used SVM to classify air quality levels and applied SVM, 1-layer NN, and boosting for MNIST digit classification.

Easwari Engineering College:

MAY 2023 ∙ Vehicle number plate detection using DL. A deep learning module is used for recognizing vehicle number plates and comparing the trained data in PyTorch and TensorFlow models for real-time vehicle number plate recognition system, enhancing security solutions by accurately identifying.

AUG 2020 ∙ The semi-finalist at the National Level Innovation Challenge, conducted by the Ministry of Education innovation cell, 2020. Intelligent Water Conservation An IoT-based water monitoring system for distributing water to every individual through a controlled flow.

Activities:

AUG 2020 - 2023 ∙ Secretary of the club Youth Red Cross – Easwari Engineering College.

MAY 2020 ∙ Developed and maintaining a website CubeXalphA Review the tech gadgets.

FEB 2020 ∙ Kaizen Robotics program - Lema Labs, IITM Research Park for 3 months.

Honors & Awards:

• Semi-Finalist – IIC National Innovation Contest 2020

  Issued by Ministry of Education's Innovation Cell, New Delhi · Dec 2021 Selected as a semi-finalist for the Business Plan Development stage with mentoring support, representing Easwari Engineering College.

• Campus E-Leader – Student Entrepreneurship Programme

  Issued by EDII-TN & Anna University, MIT - IEDP Hub · Sep 2020 Represented Easwari Engineering College's E-Cell as Campus E-Leader in the entrepreneurship initiative conducted by EDII-TN, MIT - IEDP Hub, and E-Cell IIT Madras.

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