Summary
Overview
Work History
Education
Skills
Projects
Timeline
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KALLURU BHAVESH

Chicago,IL

Summary

GenAI Engineer and AI Engineer Expert with a solid background in building scalable AI and ML applications. Demonstrated proficiency in Python, Deep Learning, and NLP, with successful deployment of models in real-world scenarios. Eager to join innovative tech companies to drive technological progress and enhance AI capabilities.

Overview

4
4
years of professional experience

Work History

AI ENGINEER

Trine University
, Michigan
08.2023 - 07.2025
  • Smart Prompter
  • AI-powered prompt generator that crafts high-quality prompts from minimal input.
  • Built a streamlined application that converts user keywords into optimized AI prompts using GPT-4, reducing prompt engineering effort by 90%.
  • Implemented prompt refinement using NLP techniques and user intent classification, enabling consistent high-quality LLM outputs.
  • Designed for both technical and non-technical users with an intuitive interface, increasing adoption and prompt reuse across early testers.
  • Lyra AI Assistant (macOS)
  • AI desktop assistant built with Python and Tkinter, designed for macOS users.
  • Created a lightweight personal AI assistant using GPT-3/5.4 and Tkinter for macOS, capable of handling daily tasks and queries offline.
  • Implemented modular functions including notes, summaries, and question answering with a clean, no-cloud UI layer.
  • Optimized for speed and performance on local machines without heavy dependencies.
  • Brand Catcher Game
  • Interactive game built using Python for brand recognition and learning.
  • Built a mini game to test and improve brand recognition, using Python’s object-oriented features and event handling.
  • Designed an interactive UI with score tracking and time-based difficulty scaling, making it suitable for edutainment use.
  • Packaged and deployed for offline use with plug-and-play simplicity.

ASSISTANT SYSTEM ENGINEER

Tata Consultancy Services
Bangalore
08.2022 - 08.2023
  • Developed and optimized machine learning models (regression, classification, clustering) using Python (scikit-learn, XGBoost) to drive data-driven decision-making across banking and telecom domains.
  • Designed and implemented deep learning models using TensorFlow and PyTorch for tasks like image recognition, document classification, and predictive maintenance, achieving up to 94% accuracy.
  • Automated end-to-end model training pipelines including feature engineering, hyperparameter tuning, and model versioning, accelerating development cycles by 40%.
  • Applied Natural Language Processing (NLP) for chat log analysis, sentiment detection, and smart ticket classification using spaCy, Transformers, and BERT-based models.
  • Built and deployed RESTful APIs for ML models using FastAPI and Docker, enabling seamless integration of models into enterprise applications and front-end dashboards.
  • Conducted model performance evaluations using cross-validation, confusion matrices, AUC/ROC, and precision-recall metrics to ensure robust and explainable predictions.
  • Collaborated with cross-functional teams (data engineers, domain experts, and PMs) to deploy scalable AI solutions in production, supporting systems with millions of data points daily.

ML ENGINEER INTERN

Besant Technologies
Bangalore
12.2021 - 06.2022
  • Designed and deployed real-time machine learning pipelines using Python, Kafka, and TensorFlow Serving, reducing model inference latency by 45% and supporting high throughput streaming data at scale.
  • Improved model training speed by 60% by implementing feature store optimization and data pipeline parallelization using Pandas.
  • Built a CI/CD workflow for ML models using GitHub Actions, Docker, and MLflow, enabling automatic retraining and deployment, which reduced production downtime by 90%.
  • Deployed a real-time anomaly detection system for financial transactions using Autoencoders and Isolation Forests, identifying fraud patterns with 98% precision and minimizing false positives by 30%.
  • Refactored legacy ML codebase to modular, testable components, improving code reusability and reducing bug-related rollbacks by 70% in production environments.

Education

Master’s - Computer Science

Trine University
Michigan
08.2025

Bachelor of Technology - Mechanical Engineering

JNTU
Anantapur
08.2021

Skills

  • Programming languages: Python, JavaScript, SQL
  • AI/ML frameworks: TensorFlow, PyTorch, Transformers, Hugging Face
  • Web and API development: FastAPI, Streamlit, Flask, and REST APIs
  • Databases & Cloud: MySQL
  • Tools and platforms: GitHub, VS Code, Jupyter Notebook
  • Visualization and BI tools: Power BI, Matplotlib, Seaborn
  • GenAI and NLP: OpenAI API, LangChain, spaCy, GPT, Gemini, and prompt engineering

Projects

YouTube Summarization using Gemini LLM

Developed an automated YouTube video summarization system using Gemini LLM, enabling quick content digestion from long-form videos.

Integrated transcript extraction APIs to retrieve video captions and passed them through a large language model pipeline for real-time summarization.

Built and deployed a scalable pipeline using Python, Fast API, and prompt engineering, ensuring summaries were accurate and content aware.

Enhanced summarization performance by fine-tuning Gemini prompts for informative, concise, and human-like output, reducing manual content review by 80%.

Designed the system for plug-and-play API usage, making it deployable across platforms like Slack, Chrome Extensions, and internal dashboards.

Power BI Dashboard for Data Professionals Survey

Power BI Dashboard – Data Professionals Survey Analysis, Designed an interactive Power BI dashboard analyzing survey responses from 1,000+ global data professionals across roles, tools, and salaries.

Integrated data cleaning, transformation, and modeling using Power Query and DAX to build dynamic relationships and drill-down capabilities.

Visualized key insights such as salary trends by role and region, tool popularity (Python, R, SQL, Power BI), and skill distribution across experience levels.

Enabled slicers, bookmarks, and cross-filtering to allow end users to explore insights by job title, industry, location, and years of experience.

Delivered actionable insights for aspiring data professionals and hiring managers, showcasing storytelling with data through clean UX and KPI-driven design.

Timeline

AI ENGINEER

Trine University
08.2023 - 07.2025

ASSISTANT SYSTEM ENGINEER

Tata Consultancy Services
08.2022 - 08.2023

ML ENGINEER INTERN

Besant Technologies
12.2021 - 06.2022

Master’s - Computer Science

Trine University

Bachelor of Technology - Mechanical Engineering

JNTU

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KALLURU BHAVESH