AI/ML Engineer | Data Engineer | Backend Engineer | GenAI Engineer | Building Scalable & Intelligent Systems
Specialized in designing scalable backend systems, cloud-native data pipelines, and intelligent AI/ML solutions that deliver measurable business impact.
I am a results-driven AI/ML Engineer, Data Engineer, Backend Engineer, and GenAI Engineer with 2+ years of professional experience building scalable backend systems, high-performance data pipelines, and production-ready AI solutions. I hold a Bachelor’s (BCA) and Master’s (MCA) in Computer Applications and have authored four research papers in AI/ML, including two published by Springer.
My expertise spans AWS-based data engineering (Glue, Lambda, Step Functions, Athena, RDS), Python backend development (Django, Flask, FastAPI, PostgreSQL), and enterprise ETL/ELT workflows across AWS and Azure. I specialize in machine learning, deep learning, Generative AI, NLP, LLM, and computer vision, delivering end-to-end systems that drive automation, intelligence, and measurable business outcomes.
With a portfolio of 15+ impactful projects across AI & ML, Web Applications, Android applications, and system software, I bring strong engineering depth, research experience, and a product-focused mindset. I am currently seeking fully remote global opportunities as an AI Engineer, Data Engineer, Backend Engineer (Python), GenAI Engineer, or Machine Learning Engineer..
Professional Experience
1
AI Engineer - Vector ML Analytics
June 2025 - September 2025 | New York, USA (Remote)
Designed and deployed production-grade AI agents, LLM-powered systems, and autonomous GenAI workflows that automated complex financial analytics, reporting, and enterprise decision-making processes.
Engineered advanced RAG pipelines and embeddings-driven retrieval architectures to deliver intelligent contextual search, financial reasoning, and real-time insights across large-scale enterprise datasets.
Architected scalable multi-client AI infrastructure integrating AWS cloud services, PostgreSQL, GitHub automation pipelines, and high-performance backend APIs for enterprise-grade AI operations.
Built reusable AI agent frameworks capable of orchestrating diverse financial workflows and processing large-volume structured and unstructured data with high reliability and scalability.
Optimized enterprise AI and ETL workflows, reducing processing latency from minutes to seconds while improving operational efficiency, automation accuracy, and reporting performance.
Collaborated with R&D and product teams to integrate Generative AI capabilities into financial platforms, enabling intelligent automation, scalable AI adoption, and faster data-driven decision-making.
Contributed to the development of cloud-native AI systems focused on scalability, reliability, maintainability, and production-ready deployment across multiple enterprise client environments.
2
Data Engineer - Vector ML Analytics
December 2024 - September 2025 | New York, USA (Remote)
Designed and deployed scalable AWS-based data engineering pipelines using Glue, Lambda, Step Functions, Athena, EC2, RDS, and IAM to process large-scale structured and unstructured enterprise datasets efficiently.
Engineered high-performance ETL/ELT workflows integrating multiple data sources, enabling reliable data ingestion, transformation, orchestration, and analytics across financial systems and reporting platforms.
Developed robust backend data services and analytics infrastructures using Python, Django, PostgreSQL, and REST APIs to power data-driven financial applications and intelligent reporting workflows.
Optimized cloud-native data pipelines and processing architectures, reducing workflow latency by approximately 30% while improving scalability, reliability, and operational performance in production environments.
Collaborated with enterprise clients and cross-functional engineering teams to design domain-specific financial data models, analytics solutions, and ML-integrated automation workflows for enhanced business intelligence and decision-making.
Built scalable data systems supporting analytics, reporting, AI/ML pipelines, and enterprise automation workflows, enabling faster insights generation and improved operational efficiency.
Contributed to the development of secure, maintainable, and production-grade cloud data infrastructures aligned with enterprise scalability, performance, and reliability standards.
3
Full Stack Developer - Pinaca Technologies
April 2024 - May 2024 | Hyderabad, India (On Site)
Developed and maintained scalable backend systems and web application architectures using Python, Django, Flask, and FastAPI for data-driven business applications.
Designed and implemented high-performance RESTful APIs and backend services enabling seamless communication between frontend interfaces, databases, and enterprise application workflows.
Integrated and optimized relational and NoSQL database systems including MS SQL Server and MongoDB to ensure efficient data management, scalability, and high-speed query performance.
Contributed to backend architecture enhancements focused on application scalability, maintainability, performance optimization, and production reliability.
Collaborated with frontend developers and deployment teams to deliver fully integrated full-stack applications with stable production deployments and seamless user experiences.
Participated in system design, API development, debugging, and deployment workflows while following clean coding practices and scalable software engineering standards.
4
Machine Learning Engineer Intern - Refactor Academy
August 2022 - June 2023 | Bangalore, India (Remote)
Designed, trained, and evaluated machine learning models using supervised and unsupervised learning algorithms for predictive analytics and data-driven business solutions.
Performed advanced feature engineering, hyperparameter tuning, model optimization, and cross-validation techniques to improve model accuracy, generalization, and performance on real-world datasets.
Developed end-to-end predictive analytics solutions including E-Commerce Customer Analysis achieving 98% R² accuracy using advanced regression techniques and Mall Customer Segmentation using K-Means clustering with a 0.4486 silhouette coefficient score.
Built scalable ML workflows and data processing pipelines using Python, Pandas, NumPy, Scikit-Learn, and data visualization libraries for data analysis, model training, and performance evaluation.
Applied machine learning techniques including regression models, clustering algorithms, decision trees, random forests, boosting methods, and statistical analysis to extract actionable insights from complex datasets.
Collaborated on real-world ML projects involving data preprocessing, exploratory data analysis (EDA), model experimentation, and predictive solution development for business-oriented use cases.
5
Python Development Intern - Skills Cafe
February 2020 - June 2020 | Pune, India (On Site)
Developed desktop-based applications and automation tools using Python, Tkinter, and OpenCV for internal productivity and workflow optimization use cases.
Designed and implemented GUI-based software applications focused on usability, functionality, and process automation across image processing and text-based utility systems.
Built multiple Python applications including Image Converter, Image Rotation, and Notepad systems with image manipulation, file handling, and user-interactive features.
Applied core Python programming concepts, GUI development practices, and image processing techniques to create lightweight and efficient desktop solutions.
Contributed to application testing, debugging, and performance improvements while following structured software development and problem-solving approaches.
Gandhi Institute for Technology, Bhubaneswar (BPUT University)
CGPA: 8.51/10 | 2020-2022
2
Bachelor of Computer Applications
Tilak Maharashtra Vidyapeeth, Pune
CGPA: 8.48/10 | 2017-2020
Research Papers
Published Papers
1
Diagnosis of Plant Diseases By Image Processing Model For Sustainable Solutions
Published in Springer (ICISML)
Developed a predictive model for diagnosing plant diseases using image analysis and machine learning to analyze RGB images and identify diseases, recommending sustainable solutions. Employed Convolutional Neural Networks (CNNs) and the VGG19 model for accurate disease detection, creating an effective AI framework for plant health diagnosis.
Empirical Analysis of Contextual Factors in Native Mobile App Development: A Case Study of E-Commerce Applications
Published in Springer (BITMDM)
Investigated the impact of contextual factors (device, user behavior, mobility, and social data) in the development of native e-commerce apps. Built a process model for mobile app development validated using customer feedback and statistical ML methods.
Developed a predictive healthcare model using machine learning and deep learning techniques to analyze maternal health data and predict delivery outcomes. Built classification algorithms to assess risk factors and predict whether pregnant women will require normal delivery or cesarean section based on comprehensive health indicators and demographic data. The model aims to assist healthcare professionals in early risk assessment and treatment planning for improved maternal and neonatal outcomes.
2
Breast Cancer Tumor Classification
Research Paper (Accepted)
Built a diagnostic tool to classify tumors as benign or malignant using machine learning algorithms including SVM, Logistic Regression, and Random Forest. The research focuses on early detection and treatment planning through automated classification of breast cancer tumors, contributing to improved diagnostic accuracy and patient care outcomes.
Featured AI/ML Projects
E-commerce Customer Data Analysis
Developed a predictive analytics solution to analyze e-commerce customer behavior, purchasing patterns, and revenue trends using advanced exploratory data analysis (EDA) and machine learning techniques.
Implemented regression models including L1-Lasso, L2-Ridge, and Elastic Net, achieving 98% R² accuracy for customer value prediction and business forecasting.
Applied advanced ML algorithms including Random Forest, Decision Trees, Boosting Techniques, Clustering, SVM, and PCA to uncover actionable business insights and improve decision-making processes.
Technologies: Python, Machine Learning (Regression Models, Boosting Techniques, Decision Tree, Random Forest, Clustering, SVM, PCA), Deep Learning
Built an intelligent diagnostic system for breast cancer tumor classification using supervised machine learning algorithms including SVM, Logistic Regression, and Random Forest.
Developed predictive models capable of classifying tumors as benign or malignant to support early diagnosis and treatment planning. Performed data preprocessing, feature engineering, model evaluation, and performance optimization to improve classification accuracy and reliability in healthcare analytics applications.
Technologies: Python, Scikit-Learn, Pandas, Machine Learning, Data Analysis
Credit Card Customer Performance Analysis
Developed a predictive banking analytics model to classify customers based on profitability, financial behavior, and engagement patterns.
Applied supervised machine learning techniques and data analysis workflows to identify high-value customers, improve retention strategies, and support targeted financial decision-making processes for banking operations.
Technologies: Python, Machine Learning, Predictive Analytics, Pandas, Data Analysis
Performed large-scale stock market trend analysis and predictive forecasting using 30 years of historical financial market data integrated through Yahoo Finance API.
Built regression-based predictive models and data visualization dashboards to analyze market behavior, identify investment patterns, and generate financial insights for data-driven investment strategies.
Developed a healthcare-focused predictive analytics system using Logistic Regression and GridSearchCV to identify individuals at high risk of diabetes based on medical and demographic attributes.
Applied hyperparameter tuning, feature optimization, and model evaluation techniques to improve prediction accuracy and support early healthcare risk assessment.
Analyzed over 2 million beauty product reviews using machine learning and sentiment analysis techniques to identify customer preferences, review trends, and product feedback patterns.
Performed exploratory data analysis (EDA) and implemented AdaBoost and XGBoost algorithms to generate actionable insights supporting product optimization and marketing strategies.
Developed an intelligent document-aware chatbot capable of answering historical questions using Retrieval-Augmented Generation (RAG) architecture with LangChain and Pinecone vector database integration.
Leveraged OpenAI LLMs for contextual understanding, semantic search, and natural language response generation to deliver accurate and conversational historical information retrieval.
Built an NLP-powered news analytics application capable of summarizing global news articles and performing sentiment analysis using Hugging Face models, TextBlob, and OpenAI pre-trained language models.
Implemented automated text processing pipelines for intelligent content summarization, sentiment detection, and real-time news analysis workflows.
Developed machine learning-driven logistics optimization solutions for U.S.-based delivery operations using geolocation event data and predictive analytics techniques.
Built models to identify delivery delays, optimize routing efficiency, and improve operational performance across large-scale logistics workflows.
Technologies: Python, Pandas, Machine Learning, Predictive Analytics, Data Analysis
Developed an Artificial Neural Network (ANN)-based predictive analytics model for weather data classification and performance evaluation.
Conducted model training, testing, and confusion matrix analysis achieving TP=13, TN=2, FP=5, and FN=0 while evaluating classification accuracy and predictive model performance.
Technologies: Python, Machine Learning, Deep Learning (ANN), Data Analysis
Developed a full-stack online learning platform enabling students to access educational resources, explore technology-focused courses, track learning progress, and enhance technical skills through an interactive digital learning environment.
Designed intuitive user interfaces and scalable backend systems to improve accessibility, course management, and user engagement for online education workflows.
Built a tourism management platform offering curated travel packages across Odisha with customizable destination planning and personalized travel experiences.
Developed dynamic package management systems, interactive travel interfaces, and data visualization features to improve user engagement and simplify travel planning workflows for tourists.
Technologies: HTML5, CSS3, JavaScript, React.JS, Python, Django, PostgreSQL, Data Visualization
Tour Guides Assignment Management
Developed a web-based guide management and assignment system enabling tourists to book travel guides and manage personalized travel experiences efficiently.
Implemented backend workflows for guide allocation, booking management, and operational coordination to improve customer satisfaction and assignment efficiency.
Designed and developed a productivity-focused task management platform supporting personal and team-based workflow organization, task categorization, deadlines, and real-time status updates.
Built scalable backend APIs and interactive frontend interfaces to improve collaboration, productivity tracking, and workflow management efficiency.
Built a secure real-time video communication platform supporting one-to-one virtual meetings, live messaging, authentication, and collaboration features for remote communication workflows.
Integrated real-time streaming and cloud-based backend services to ensure seamless communication performance and secure user interactions.
Technologies: HTML5, CSS3, JavaScript, React.JS, Node.JS, Google Firebase Firestore
Developed a web-based vehicle service management platform enabling users to schedule service appointments, track maintenance requests, and manage service histories efficiently.
Designed user-friendly booking workflows and backend management systems to streamline operations for vehicle service centers and improve customer experience.
Built a blood donation and request management platform using Django to streamline donor registration, blood inventory tracking, and emergency blood request processes.
Developed secure and user-friendly workflows enabling hospitals, donors, and organizations to efficiently manage blood availability and improve timely access to critical healthcare resources.
Developed a real-time women safety application enabling users to instantly share live location data and emergency alerts with police authorities, family members, and trusted contacts during critical situations.
Built secure emergency communication workflows with real-time tracking capabilities to improve personal safety, rapid response coordination, and emergency assistance accessibility.
Built a comprehensive digital village management platform designed to improve communication, accessibility, and community services for rural populations.
Developed modules for population management, annual profit tracking, government notice distribution, support communication, and online shopping functionalities to enhance digital accessibility and operational efficiency within village ecosystems..
Developed a food pre-ordering mobile application for TMV College canteen enabling students to place meal orders in advance and reduce waiting times during peak lunch hours.
Designed efficient order management workflows allowing food preparation before student arrival, improving operational efficiency and enhancing the user dining experience.
Built a digital student feedback management system for educational institutions to automate lecture feedback collection, analysis, and reporting workflows.
Replaced traditional paper-based feedback systems with secure digital processes including user authentication, feedback submission, rating analysis, and administrative reporting dashboards for improved academic evaluation and operational efficiency.
Technologies: Core Java, Advanced Java, Data Mining, Rating Analysis, Android, XML, SQLite, Google Cloud
Crime File Management System (College Project)
Developed a secure criminal records management platform for police departments featuring encrypted inter-station communication, secure record management, and data recovery capabilities.
Implemented encryption and decryption mechanisms to ensure secure information exchange and improve operational reliability across law enforcement workflows.
Technologies: VB.NET, MSSQL, Encryption/Decryption Scripts, Data Recovery System
Currently developing a comprehensive Android-based hotel management application designed to streamline hotel operations, guest services, booking management, and administrative workflows.
The system includes modules for room management, customer handling, service tracking, and operational automation to improve efficiency and enhance hospitality management processes.
Rental Car Booking Platform
Building a full-stack rental car booking platform for a client featuring vehicle inventory management, real-time booking workflows, customer management systems, and secure user portals.
Developing scalable backend services and responsive user interfaces to optimize booking operations, improve customer experience, and support efficient vehicle rental management.
Lungs Tumors Classification and Cancer Detection
Developing an advanced AI-powered medical imaging analysis system for lung tumor classification and cancer detection using machine learning and deep learning techniques.
The solution focuses on early diagnosis support, automated tumor classification, and intelligent healthcare analytics to assist medical professionals in improving diagnostic accuracy and treatment planning workflows for healthcare applications.
Key Project Achievements
2
Research Papers
Published in Springer
98%
Model Accuracy
E-commerce Analysis
2M+
Reviews Analyzed
Amazon Customer Rating
0.4486
Silhouette Score
Mall Customer Segmentation
Technical Highlights
Published 2 research papers in Springer (ICISML & BITMDM) with 2 more under evaluation
Developed VGG19-based CNN model for plant disease diagnosis with sustainable solutions
Built process model for native mobile app development validated through statistical ML methods
Achieved 98% R² accuracy in e-commerce customer analysis using advanced regression techniques
Created diagnostic tool for breast cancer classification using SVM, Logistic Regression, and Random Forest
Created document-aware chatbot using LangChain, Pinecone, and OpenAI for historical question answering
Enhanced U.S. delivery operations through geolocation-based ML prediction models
Built live web applications: Ez2Learn learning portal and Odisha Tourism platform serving real users
Analyzed 2M+ beauty product reviews with AdaBoost and XGBoost for sentiment analysis
Developed predictive models for diabetes detection and credit card customer performance analysis
Segmented mall customers into 5 optimal clusters for targeted marketing strategies
Project Inquiry & Collaboration
Interested in Working Together?
I help startups, businesses, and organizations build scalable AI solutions, modern web platforms, intelligent automation systems, and high-performance backend infrastructures. Whether you need an AI-powered product, a full-stack application, cloud-based backend systems, or custom software development, I focus on delivering production-ready solutions that are scalable, reliable, and business-driven.
With expertise across AI/ML engineering, Generative AI, backend development, cloud infrastructure, and full-stack application development, I work closely with clients to transform ideas into real-world products and impactful digital solutions.
Services I Offer:
I’m available for freelance, contract, startup, and custom development projects focused on AI systems, backend engineering, scalable cloud infrastructure, and intelligent automation platforms.
AI/ML Solutions & Predictive Analytics
Generative AI Applications & LLM Integrations
AI Agents, RAG Pipelines & Intelligent Chatbots
Backend Engineering & Scalable API Development
Data Engineering & Cloud-Based Data Pipelines
Full-Stack Web Application Development
Android Application Development
Custom Software Development for Startups & Businesses
Research & AI-Based Solution Development
Whether you need an AI-powered platform, intelligent chatbot, automation system, scalable backend infrastructure, full-stack application, or end-to-end product development, I can help design and build production-ready solutions tailored to business and operational needs.
Project Inquiry Form:
Please provide the following details in mail by clicking on the connect me and I'll get back to you within 24 hours:
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Your Name: (Your name)
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Project Type: (AI Solution, Web Application, Backend System, Mobile App, Full-Stack Platform, Research Project, Other)
Let’s build intelligent, scalable, and impactful solutions together.
Let's Build Something Amazing Together
Ready to Collaborate
With expertise across AI/ML engineering, Generative AI, backend development, and cloud-based data engineering, I specialize in building scalable, production-ready systems including AI agents, LLM applications, RAG pipelines, intelligent automation platforms, and high-performance backend architectures. My experience includes Python, FastAPI, Django, Flask, AWS, PostgreSQL, OpenAI/LLMs, NLP, machine learning, and scalable API-driven systems.
I thrive in fast-paced remote environments and Agile teams, focusing on transforming complex requirements into clean architectures, intelligent automation workflows, and business-driven solutions. Whether developing AI-powered platforms, optimizing cloud data pipelines, or engineering scalable backend systems, I prioritize performance, reliability, scalability, and measurable impact.