Help & Supportcareers@gravityer.com
AI Engineer with less than a year in Machine Learning, Web Development, and MLOps.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Geetha Pranay is an aspiring AI Engineer with a focus on machine learning and full-stack web development. Currently pursuing a B.Tech in Mechanical Engineering, Geetha demonstrates strong skills in Python, FastAPI, ReactJS, and various AI/ML frameworks like PyTorch and LangChain. With experience in building web applications for predictive models and AI assistants, and contributions to open source projects, Geetha is a proactive learner with practical implementation skills.
VELLORE INSTITUTE OF TECHNOLOGY
B.Tech · Mechanical Engineering
August 1, 2023 – June 30, 2027
Concrete Strength Prediction Web Application
January 1, 2026 – June 1, 2026
Built a machine learning web application to predict concrete compressive strength from mix proportions and curing age. Trained and evaluated multiple regression models, selected XGBoost as the best performer, and achieved an R² score of about 0.90. Deployed the model with a Flask backend and Bootstrap-based front end, enabling users to enter mix values and get instant strength predictions.
Teaching AI Assistant
January 1, 2026 – June 1, 2026
Developed a full-stack educational web application using FastAPI and Streamlit, featuring secure user authentication that allows students and teachers to upload, organize, and interact with their study materials. Engineered a RAG pipeline with LangChain and Pinecone vector databases to instantly process, store, and accurately search through long PDF textbooks and notes. Integrated fast AI language models to provide instant answers to user questions and automatically generate custom practice quizzes based strictly on the uploaded documents.
Trane Techonologies (HVAC) Hackathon
January 1, 2026 – June 1, 2026
Built an ML-powered HVAC refrigerant leak detection and predictive maintenance solution using pressure, superheat, subcooling, and energy metrics won ₹50,000 as prize money.
precice/micro-manager Pull Request
January 1, 2026 – June 1, 2026
Open source contribution to precice/micro-manager.
View Projectprecice/tutorials Pull Request
January 1, 2026 – June 1, 2026
Open source contribution to precice/tutorials.
View Projectapache/fory Pull Request
January 1, 2026 – June 1, 2026
Open source contribution to apache/fory.
View Projectapache/datafusion Pull Request
January 1, 2026 – June 1, 2026
Open source contribution to apache/datafusion.
View Projectcs50(AI)
Unknown
June 1, 2026 – Present
DSA by apna college
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in applying AI/ML to solve practical problems, from predictive maintenance to educational tools. Participation in hackathons and open-source contributions indicates a proactive, curious, and collaborative mindset, which generally aligns well with a dynamic tech culture. The diversity of projects, though academic, shows a breadth of interest in different AI applications. However, the lack of professional experience means cultural fit is primarily inferred from project engagement and self-reported skills.
Soft Skills & Operational Fit
The candidate lists 'Team player' and 'Deliver results' as soft skills. Project descriptions suggest an ability to execute and deliver functional applications. The open-source contributions also hint at collaboration and adherence to project guidelines. However, without specific behavioral assessment data, a deeper evaluation of operational fit and soft skills is limited.