AI Engineer with less than a year in Computer Vision & Full-Stack Development
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI/ML Engineer skilled in Python with hands-on experience in Computer Vision, Machine Learning, and full-stack development. Built real-time monitoring systems using YOLOv5, OpenCV, Flask, and React.js. Familiar with Generative AI concepts including LLMs, Prompt Engineering, embeddings, and RAG fundamentals. Seeking opportunities in AI Engineer / GenAI Engineer roles.
Ganpat University
B.Tech · Computer Science Engineering
August 1, 2021 – June 30, 2025
Sri Chaitanya Junior College
Class XII (MPC)
June 1, 2019 – May 31, 2021
Neo Vision School
Class X (SSC)
N/A – May 31, 2019
Credit Card Fraud Detection
June 3, 2026 – Present
Built ML model to classify fraudulent vs. non-fraudulent transactions using Scikit-learn. Performed data preprocessing, feature scaling, train-test split, and evaluated results using Precision, Recall, F1-score. Reduced false positives by tuning hyperparameters and improving model generalization.
Stock Price Prediction
June 3, 2026 – Present
Developed stock forecasting model using historical data with Pandas, NumPy, and regression techniques. Visualized trends using Matplotlib and evaluated prediction error using RMSE / MAE.
Build Track – AI Construction Monitoring System
June 3, 2026 – Present
Designed and developed a real-time construction safety monitoring system using YOLOv5 + OpenCV for helmet detection. Built full-stack dashboard using Flask (API backend) + React.js (frontend) with live stream display and alert tracking. Integrated Twilio SMS API for instant safety violation alerts and anomaly notifications. Achieved 90% accuracy and optimized inference pipeline to deliver <1.5 seconds latency.
Python Training
Besant Technologies
June 1, 2026 – Present
The Complete Python Bootcamp
Udemy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying AI/ML concepts. The diversity of projects (computer vision, fraud detection, time series) indicates a broad interest within AI. However, all projects are academic, and there is no professional experience, which might impact immediate cultural integration into a fast-paced industry environment without mentorship.
Soft Skills & Operational Fit
The candidate lists communication, adaptability, fast learner, problem-solving, and team collaboration as soft skills. While these are valuable, there is no assessment data to validate their proficiency. The project descriptions indicate an ability to work on complex tasks and integrate various technologies, suggesting problem-solving and adaptability.