Software Engineer | AI/ML & Computer Vision | Full-Stack Developer
Software Engineer with 5+ years of experience building data-driven, AI, machine learning, and computer vision enabled backend systems and industrial automation solutions. Expert in Python, Java, Spring Boot, AWS, and CI/CD pipelines, with strong background in PLC-integrated systems leveraging OPCDA/OPCUA and scalable APIs.
Software Engineer with 5+ years of hands-on experience building data-driven, AI, machine learning, and computer vision enabled backend systems and industrial automation solutions. Currently at Integral Systems, Inc., implementing computer vision features, full-stack web and mobile applications, and CRM tools using React, Python (Django/Flask), and Databricks.
I specialize in Python, Java, JavaScript, Spring Boot, and AWS, with expertise in computer vision, NLP, RAG systems, and PLC-integrated industrial automation (OPCDA/OPCUA). My experience spans from building ML-powered document processing systems at UWM and Cognizant, to developing real-time industrial automation software at Comau with Jenkins, Docker, and microservices.
I hold a Master of Science in Computer Science from the University of Wisconsin-Milwaukee, where I was awarded the Chancellor's Graduate Student Award. My research focused on a full-stack AI system for automating graduate admission document extraction, summarization, and evaluation, significantly improving faculty review efficiency.
Developed a computer vision system to detect milk bottles and caps on a moving conveyor belt, simulating real-world industrial production conditions. Used Autodistill with Grounded SAM for automatic labeling, trained YOLOv8 for accurate real-time detection, and performed video-based inference for manufacturing quality control and automation integration.
Developed an AI-driven question-answering system using Retrieval-Augmented Generation (RAG), combining document retrieval and natural language generation. Implemented FAISS for efficient vector embeddings and T5 transformers for context-aware answers.
Flask-based web application that predicts graduate admission chances by extracting and analyzing scanned SOP and LOR PDFs using OCR and NLP. Achieved MAE of 0.05 and R² of 0.82, improving faculty review efficiency by 60%.
Led development of a voice-activated quiz platform using Angular, JavaScript, and Spring Boot, improving accessibility by 95% for visually and motor-impaired users. Increased user engagement by 40% with adaptive UI themes and advanced speech recognition.
Developed microservices-based MES platform with real-time monitoring using Java Spring Boot and REST APIs. Improved manufacturing efficiency by 40% and enhanced data storage efficiency by 25% through MongoDB and PostgreSQL integration.
I provide comprehensive technology solutions to help your business grow
RAG systems, multi-agent AI platforms, NLP/OCR solutions, and machine learning models for intelligent automation.
Enterprise applications using Spring Boot, Flask, Angular, React Native. Backend systems with REST/SOAP APIs.
Databricks-based data processing, ETL pipelines, CRM systems, and large-scale analytics supporting ML-driven features.
AWS/Azure deployment, Docker/Kubernetes orchestration, CI/CD pipelines, and infrastructure automation.
Object detection, quality control systems, PLC integration with OPCDA/OPCUA, and real-time monitoring for manufacturing and industrial environments.
Microservices architecture, message queues (RabbitMQ, Kafka), database integration, and legacy system modernization.
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University of Wisconsin-Milwaukee
May 2025
Relevant Coursework: Data Structures & Algorithms, Object-Oriented Programming, Machine Learning
Achievements: Graduate Teaching Assistant, Awarded the Chancellor's Graduate Student Award
Generative AI Engineer, Data Engineer Professional & Associate
Developer Certification
Building Scalable Java Microservices Certification
RHCSA Certification
Examination Paper Setter Automation (SW-12888/2019), Card Payment Three-Way Security (JETIR 2020)
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