Help & Supportcareers@gravityer.com
Final-year CSE | C++ & DSA | Exploring AI/ML | Building practical solutions
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
geo-audit-api
March 30, 2026 – Present
Beginner-friendly prototype that analyzes a webpage URL, extracts key metadata, and generates a structured GEO audit with JSON-LD recommendations for AI search visibility. Built with FastAPI, showcasing practical Python backend skills in web scraping, data processing, and API development.
View ProjectchromeExtension_QuestionAutoUploader
February 22, 2026 – Present
Uploads completed questions to GiTHUB and gets AI feedback
View Projectsmart-shopping-search
December 29, 2025 – Present
Multimodal Product Recommender is a cloud-ready React + Vite frontend that enables product discovery using text and image-based search. It displays four popular products on initial load and dynamically updates results based on user input, with a scalable architecture for future API and AI integration.
View ProjectSmartSuggest
August 24, 2025 – August 28, 2025
A next-generation AI agent that lives on-device—always available, context-aware, and proactive. It sees what you see, hears what you hear, and remembers your experiences to provide real-time, personalized assistance without needing a constant cloud connection.
View ProjectMalimg-Classifier-Benchmark
July 31, 2025 – Present
Comparative analysis of classification models on the Malimg dataset using Neural Networks, AutoML, and hyperparameter optimization (Optuna and others). Evaluates training time, accuracy, and epochs before and after tuning to study efficiency and performance improvements.
View Projectpdf-to-fhir-pipeline
July 13, 2025 – Present
A pipeline that uses Optical Character Recognition (OCR) to extract structured data from unstructured medical PDFs and transforms it into standard FHIR format for healthcare interoperability.
View ProjectGenomic-and-Clinical-ML-Cancer-Prediction-Model
July 13, 2025 – Present
A comprehensive machine learning project analyzing cancer data through multiple modeling approaches, progressing from Kaggle datasets to real-world WHO data for clinical insights.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards personal projects and self-driven learning, which can be a positive indicator for a culture that values initiative. The diversity of projects, from healthcare data processing to e-commerce recommenders and AI agents, suggests adaptability and a broad interest in applying data science across different domains. However, the lack of team-based projects or professional experience makes it difficult to fully assess cultural fit in a collaborative work environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions indicate a proactive and self-directed learning approach, but there is no information on teamwork, communication style, or problem-solving under pressure.