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AI Engineer with less than a year in Machine Learning & Deep Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI & ML Engineering student with hands-on experience in Artificial Intelligence, Machine Learning, Deep Learning, app development and IOT systems. Proficient in Python, TensorFlow, CNNs, Flutter, and Firebase. Experienced in building end-to-end ML solutions, real-time prediction systems, and scalable mobile applications. Strong interest in applying AI-driven solutions to real-world problems.
University College of Engineering and Technology for Women, Kakatiya University
Bachelor of Technology (B.Tech) · Artificial Intelligence & Machine Learning
August 1, 2022 – June 30, 2026
VibexSuperapp
AIML Engineer Intern
January 1, 2026 – Present
India
VibexSuperapp
Flutter Frontend Developer Intern
June 1, 2025 – December 31, 2025
India
National Institute of Technology, Warangal
Internet of Things (IoT) Intern
November 18, 2024 – December 13, 2024
Warangal, Telangana, India
Farm TO Home: A Mobile App for Farmers
June 1, 2025 – June 30, 2026
Developed a mobile app enabling farmers to connect with buyers, eliminating intermediaries and improving market accessibility. Enhanced farmer profitability and reduced post-harvest losses by streamlining transactions and optimizing the supply chain. Role: Frontend Developer and Backend Developer
Telecom Customer Churn Prediction using CNN & Explainable AI
June 1, 2025 – June 30, 2026
Developed an end-to-end customer churn prediction system using a CNN with residual connections and feature-level attention. Performed data preprocessing, handled class imbalance, and applied stratified cross-validation. evaluated model performance using ROC-AUC and classification metrics. Integrated AI (SHAP) to interpret model predictions and visualize feature importance through an interactive Streamlit dashboard.
Image Classification using CNN with Real-Time Prediction
June 1, 2025 – June 30, 2026
Designed and trained a Convolutional Neural Network on the CIFAR-10 dataset. Applied data augmentation, batch normalization, and dropout to improve generalization. Integrated OpenCV for real-time webcam-based image classification and deployed the trained model for live inference. Evaluated model performance using accuracy, confusion matrix, and classification reports, achieving over 85% test accuracy data.
Topic Modeling on Text Data using LDA
June 1, 2025 – June 30, 2026
Implemented topic modeling using Latent Dirichlet Allocation (LDA) to discover latent themes in large text corpora. Applied NLP preprocessing techniques including tokenization, stop-word removal, and vectorization for effective topic extraction Analyzed and interpreted topic distributions to gain insights into underlying textual patterns.
Cultural Fit Analysis
The candidate's projects demonstrate a diverse interest in AI/ML applications (churn prediction, image classification, topic modeling) and even mobile app development. The internship experiences, including an IoT internship, show a breadth of technical exposure. While the target role is AI Engineer, the candidate's background aligns well with a learning-oriented and technically curious environment. The academic projects are well-defined and show initiative, which is a positive indicator for cultural fit in an innovative team.
Soft Skills & Operational Fit
The candidate's project descriptions suggest an ability to work on complex problems and integrate various technologies. The 'Farm TO Home' project indicates an understanding of full-stack development, which implies a collaborative mindset. However, without specific psychometric or English test scores, a detailed assessment of soft skills and operational fit is limited. The academic nature of most projects suggests a strong learning aptitude.