Help & Supportcareers@gravityer.com
AI Engineer with less than a year in Deep Learning Models & Data Analysis
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
B.Tech graduate in Artificial Intelligence & Machine Learning with experience developing machine learning models, Flask web applications, and data analysis solutions. Skilled in Python, Scikit-learn, TensorFlow, SQL, and Git with hands-on experience in phishing detection, crime prediction, and deep learning projects. Strong foundation in Data Structures, OOP, DBMS, model training, and deployment.
Malla Reddy College of Engineering and Technology, Hyderabad
B.Tech · CSE (Artificial Intelligence & Machine Learning)
August 1, 2022 – June 30, 2026
Protein 3D Structure Prediction using Clustering Deep RNN
January 1, 2025 – June 1, 2026
Developed a Clustering Recurrent Neural Network (CRNN) model to predict protein structural features from amino acid sequences. Performed data preprocessing and feature extraction on Protein Data Bank (PDB) datasets for model training. Applied clustering algorithms to group similar protein sequences and improve prediction efficiency. Implemented RNN-based deep learning models to analyze sequential biological data and identify structural patterns. Evaluated model performance using training and validation metrics to optimize prediction accuracy.
Real-Time Phishing Detection System
January 1, 2024 – June 1, 2025
Built a machine learning system to classify phishing and legitimate websites using URL-based features. Performed feature engineering using attributes such as URL length, HTTPS usage, domain information, and suspicious patterns. Trained and evaluated classification models including Logistic Regression and Random Forest for threat detection. Developed a Flask-based web application to provide real-time phishing prediction through a user-friendly interface. Improved model reliability through data preprocessing, testing, and validation on multiple URL samples.
View ProjectCrime Data Analysis and Prediction
January 1, 2023 – June 1, 2024
Analyzed historical crime datasets to identify trends, patterns, and regional crime variations across states. Performed data cleaning, preprocessing, feature engineering, and exploratory data analysis on large datasets. Built machine learning regression models to predict crime trends and support data-driven decision making. Developed a Flask application integrated with MySQL for data management, visualization, and prediction workflows. Created analytical dashboards and visual reports using Matplotlib and Seaborn to communicate insights effectively.
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and foundational skill set in Artificial Intelligence and Machine Learning, aligning well with an 'AI Engineer' target role. The diversity of projects (bioinformatics, cybersecurity, social data analysis) indicates adaptability and a broad problem-solving mindset. Participation in leadership and extracurricular activities suggests a proactive and collaborative attitude, which generally contributes positively to cultural fit. However, the lack of professional experience means cultural fit is primarily inferred from academic engagement and project types.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems, manage data, and deploy applications. Leadership and extracurricular activities suggest good organizational skills and potential for teamwork. However, without specific psychometric or English test results, a comprehensive assessment of soft skills and operational fit is limited.