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Entry-Level Full Stack Engineer with MERN stack, AI/ML, and Generative AI skills
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Full Stack Developer specializing in the MERN stack (MongoDB, Express.js, React.js, Node.js) with hands-on experience building scalable web applications, RESTful APIs, and AI/ML and Generative AI systems. Proficient in JavaScript (ES6+), React Native, Python, LLM integration (Gemini), and multi-agent AI (CrewAI). Strong Data Structures & Algorithms (DSA) skills (250+ LeetCode). Experienced in OOP, Git/GitHub, Agile, CI/CD, and cross-functional collaboration.
KIT's College of Engineering, Kolhapur
Bachelor of Technology (B.Tech) · Computer Science & Business Systems
August 1, 2023 – June 30, 2027
Vishwakarma College, Kagal
HSC · Science
June 1, 2021 – May 31, 2023
Manav High School, Shendur
SSC
June 1, 2020 – May 31, 2021
S.I.R.A. - Scam Intelligence & Response Agent
January 1, 2026 – Present
Engineered an Active Defense cybersecurity pipeline integrating an ensemble ML model (Isolation Forest, Behavioral Biometrics, LLMs) to detect phishing threats with 92.5% accuracy. Built a multi-agent autonomous system using CrewAI and Gemini LLM to engage scammers and extract structured threat intelligence (UPI IDs, phone numbers) via spaCy NER and Regex. Mapped criminal networks into a Neo4j Graph Database and integrated SHAP for Explainable AI (XAI), ensuring transparent and interpretable ML decision-making. Developed a React Native mobile interface integrated with a FastAPI backend, enabling real-time scam alerts and threat dashboards for end users.
View ProjectSkinalyze - Skin Disease Detection System
January 1, 2025 – December 31, 2025
Engineered a CNN-based deep learning model for automated skin disease classification from medical images, achieving high-accuracy multi-class prediction using TensorFlow and Python. Designed an end-to-end machine learning pipeline - data preprocessing, augmentation, model training, and hyperparameter tuning - reducing training loss by 30%. Developed a responsive full-stack web interface using HTML5, CSS3, and Flask for image upload and real-time ML predictions, integrating frontend with backend.
View ProjectYouTube Comment Sentiment Analysis
January 1, 2024 – December 31, 2024
Built an NLP-based sentiment analysis classifier to categorize YouTube comments using supervised machine learning; achieved 85%+ classification accuracy with Scikit-learn. Implemented text preprocessing pipeline: tokenization, stop-word removal, TF-IDF vectorization, and feature extraction, improving model accuracy by 18%. Trained and evaluated Logistic Regression, Random Forest, and Naive Bayes models; selected best-performing classifier using F1-score and precision-recall metrics.
View ProjectArtificial Intelligence & Machine Learning Virtual Internship
Eduskill / AWS
January 1, 2024 – Present
Introduction to Python Programming
Coursera (Google)
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from cybersecurity to healthcare and sentiment analysis, indicates a broad interest in applying technical skills to various domains. The focus on AI/ML and full-stack development aligns well with a 'Full Stack Engineer' role, especially one that might involve intelligent systems. The self-driven learning and project completion suggest a proactive and innovative mindset, which could be a good cultural fit for dynamic, tech-forward teams. However, the lack of team-based project experience or professional roles limits the assessment of collaboration and interpersonal skills.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and a proactive learning attitude through personal projects and certifications. The project descriptions suggest an ability to work independently on complex technical challenges. However, without direct work experience or behavioral assessment data, it's difficult to fully assess collaboration, communication, and stress handling in a team environment.