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AI Engineer with less than a year in Computer Vision & Deep Learning
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An ambitious AI Engineer in her final year of B.Tech in Computer Science and Engineering (Artificial Intelligence), with a strong academic record (CGPA: 8.97/10.0) and 5 months of hands-on experience as a Software Engineer Intern. Possesses expertise in deep learning models, computer vision, and machine learning, honed through impactful projects and industry experience. Eager to apply her skills in developing innovative AI solutions and optimizing complex data workflows.
Vishwakarma Institute of Technology, Pune
B.Tech · Computer Science and Engineering (Artificial Intelligence)
August 1, 2022 – June 30, 2026
Atlas Copco Group
Software Engineer Intern
February 1, 2026 – June 30, 2026
India
Basil Leaf Disease Classification System
June 1, 2026 – June 30, 2026
Developed a Basil Leaf Disease Classification System for automated identification of 5 disease categories, supporting early disease detection and precision agriculture. Implemented a hybrid deep learning approach by combining EfficientNetB0 for feature extraction with Support Vector Machine (SVM) for disease classification. Improved classification accuracy from 95.02% to 98.86% using the hybrid model, enabling more reliable disease diagnosis and informed agricultural decision-making.
Financial Transaction Anomaly Detection using Unsupervised Machine Learning
June 1, 2026 – June 30, 2026
Built an end-to-end unsupervised machine learning pipeline for financial transaction anomaly detection using feature engineering, preprocessing, and outlier detection techniques. Engineered 10+ transaction-based features from 12 raw attributes and evaluated 3 anomaly detection algorithms (Isolation Forest, Local Outlier Factor, One-Class SVM), selecting the optimal model through hyperparameter tuning. Deployed the optimized LOF model as an interactive Streamlit web application, enabling real-time anomaly detection through CSV upload, automated preprocessing, visualization dashboards, and downloadable prediction reports.
Fundamentals of Deep Learning
Nvidia
June 1, 2026 – Present
Google Cloud Computing Foundations
June 1, 2026 – Present
Google Data Analytics
June 1, 2026 – Present
Cloud Computing
NPTEL
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects showcase a diverse application of AI, from agriculture to finance, indicating adaptability and a broad interest in problem domains. Their internship at Atlas Copco Group, where their solution was adopted in-house, demonstrates a strong ability to deliver impactful results in an industrial setting. Participation in hackathons and leadership in a student club further highlight initiative, teamwork, and a commitment to continuous learning and community engagement. These aspects suggest a good cultural fit for a dynamic and innovative AI engineering team.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through their project work, tackling complex challenges like activity classification in manufacturing and financial anomaly detection. Their involvement in organizing technical workshops suggests leadership potential and a collaborative spirit. The ability to deploy interactive web applications (Streamlit) indicates a user-centric approach and practical application of technical skills. The candidate's academic background in AI and relevant certifications align well with an AI Engineer role.