Help & Supportcareers@gravityer.com
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 Engineer with less than a year in Artificial Intelligence & Applications
Highly motivated B.Tech student specializing in Artificial Intelligence and Applications, seeking opportunities in AI/ML engineering. Possessing strong skills in deep learning, machine learning, and data analysis. Demonstrated ability to build CNN models, implement object detection frameworks, and develop recommendation systems through impactful internships and academic projects. Eager to apply technical expertise to solve real-world problems and contribute to innovative solutions.
Indian Institute of Technology, Kharagpur
B.Tech · Agricultural and Food Engineering, Micro Spl. in Artificial Intelligence and Applications
August 1, 2023 – June 30, 2027
Matrix High School, Sikar
Class 12
June 1, 2021 – May 31, 2022
SEM School, Sikar
Class 10
June 1, 2019 – May 31, 2020
Typpout
Machine Learning Intern
December 1, 2025 – January 1, 2026
India
IIT Kharagpur
Research Intern | Tea Disease Detection
May 1, 2025 – July 1, 2025
Kharagpur, West Bengal, India
Food Nutrition Detection Using Deep Learning
March 1, 2026 – April 1, 2026
Objective: Developed a DL system for automated nutrition estimation from food images, leveraging a 5k dataset and CNN models • Built RGB-D preprocessing pipeline on 5k+ images using OpenCV & TensorFlow with alignment, normalization & augmentation • Standardized nutritional features (cal, fat, carbs) using per-100g normalization, 12 outlier removals, and Word2Vec embeddings • Trained a CNN model for prediction, delivering reliable results for protein 0.6 R2, outperforming baseline models SVM, k-NN
Mapping Employment-Linked Internal Migration Hotspots | UIDAI Data Hackathon 2026
January 1, 2026 – January 1, 2026
Objective: Analyzed Aadhaar address-change data to uncover internal migration patterns, flagging high employment-linked migration zones • Engineered 26 features (ADI, Relocation Stability Index) using Uni/Bi/Trivariate Analysis performed with Pandas, NumPy and GeoPandas • Performed Anomaly Detection using Isolation Forest & Rule-based Statistical Identification models and analysed trends via visualization • Quantified migration drivers via Spatio-Temporal Analysis – Employment(45%), Demographics(30%), Urban Housing(15%) using Matplotlib • Detected UIDAI Nov 2025 policy-driven 3X spike in recorded relocations through Rolling Volatility & Momentum Indicator features
E-commerce Customer Segmentation and Analysis
October 1, 2025 – November 1, 2025
Objective: Analyze customer behavior using RFM metrics, clustering & association rules to build targeted recommendation system • Conducted a detailed EDA and feature-engineered RFM metrics (recency, frequency, monetary) to assess customer behavior • Implemented K-means, DBSCAN and hierarchical clustering to identify 5 distinct groups sharing similar purchasing behaviors • Applied Apriori algorithm on the clusters to discover frequent itemsets and generate association rules for market basket analysis • Developed recommendation system with 0.82 binary accuracy & 0.74 F1 score integrating RFM segments and association rules
Telecom Customer Churn Prediction
November 1, 2024 – December 1, 2024
Objective: To predict telecom customer churn using machine learning models, enabling proactive customer retention strategies • Built and optimized customer churn prediction models using Decision Tree, Random Forest, XGBoost achieving 82% accuracy • Cleaned and preprocessed data by handling missing values, encoding categorical features, and balancing classes using SMOTE • Performed EDA with visualization and assessed model performance using accuracy, confusion matrix and cross-validation
Cultural Fit Analysis
The candidate's academic background at IIT Kharagpur, coupled with participation in hackathons and extracurricular activities, suggests a proactive and engaged individual. The diversity of projects, from telecom churn prediction to tea disease detection and migration analysis, indicates adaptability and a broad interest in applying AI to different fields. This aligns well with a culture that values continuous learning and versatile problem-solving. However, the candidate is still early in their career, and their cultural fit would benefit from further demonstration of leadership or mentorship experiences.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a structured approach to problem-solving and a focus on achieving measurable results. Participation in team-based competitions and extracurricular activities suggests good teamwork and collaboration skills. The detailed descriptions of methodologies and outcomes reflect a strong operational fit for roles requiring analytical rigor and practical application of technical skills.