Certificate for Completion of Python 3.4.3 Training

The Structured Query Language (SQL)

Convolutional Neural Networks in TensorFlow

AWS Certified Solutions Architect – Associate

Natural Language Processing in TensorFlow

Deep Learning with PyTorch : Generative Adversarial Network

An Introduction to Interactive Programming in Python (Part 1)

CERTIFICATE OF INTERNSHIP

Bachelor of Science - BS

Master's degree

Developed a production-ready chatbot using natural language processing (NLP) techniques to respond to user queries in real-time, integrating Python and TensorFlow to enhance customer interaction by 30% through personalized responses and efficient query resolution, with considerations for model serving and monitoring. • Enhanced the machine learning training pipeline by mastering data preprocessing techniques, including cleaning, formatting, and feature engineering, which improved dataset quality and contributed to a 15% increase in model accuracy. • Collaborated with a team of AI engineers and data scientists to integrate AI solutions into company products, contributing to the design and development of a neural network model for image recognition that achieved a 95% accuracy rate, and utilizing AWS Cloud Services to support model deployment considerations.

Machine Learning Engineer

- Developed 10+ RESTful APIs for a full-stack banking system using Java, Spring Boot, and MySQL.

- Improved operational efficiency by 30% by strengthening API security and data integrity mechanisms.

- Reduced backend failure rates by 25% through optimized validation and MySQL integration.

- Delivered stable product releases through close collaboration with remote QA and product teams.

Java Developer | Spring Boot, AWS, Microservices, RESTful APIs | CI/CD & Agile Practitioner

- Built and deployed an NLP chatbot with Python, TensorFlow, and NLTK, improving real-time support accuracy by 30%.

- Boosted model accuracy by 15% through data cleaning and feature engineering.

- Developed an image classification pipeline achieving 95% accuracy on internal datasets.

- Reduced manual query resolution workload by 40% by integrating ML models into core workflows.

Machine Learning Intern

- Architected and deployed a production-grade AI platform for real-time voice agents and video intelligence using Python, TypeScript, and Node.js.

- Integrated live AI agents into Zoom, Google Meet, and Microsoft Teams via WebRTC/WebSockets for real-time interaction and basic video analysis.

- Reduced model serving costs by 90% and improved system throughput through hybrid local/cloud execution and Redis caching.

- Increased deployment stability by 35% across 10+ microservices using asynchronous design and Docker containerization.

- Enabled metering-based billing and enterprise licensing workflows, unlocking $300K+ in annual contract value.

- Automated CI/CD pipelines for ML microservices using GitHub Actions, including model versioning and rollback support.

- Refined prompt structures and improved contextual accuracy of AI voice-agent responses.

AI Engineer

AI Engineer.

github

Know about Chaitanya Surabattuni's work experience, education, bootcamps, certifications, and much more. Chaitanya Surabattuni