Help & Supportcareers@gravityer.com
AI Engineer with 1+ years in AI & ML, Python, and Full-Stack Development
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Motivated 2025 computer science graduate with a strong foundation in programming, algorithms, and problem solving. Proficient in Python. Eager to contribute to team success through collaboration, continuous learning, good communication skills and applying engineering principles to solve real-world challenges.
GBPIET Pauri, Uttarakhand
B.Tech · Computer Science and Engineering (AI & ML)
August 1, 2021 – June 30, 2025
Heera Lal Public School, Delhi
Higher Secondary · XI-XII (CBSE)
June 1, 2018 – May 31, 2020
Real-Time Transit Booking Platform
January 1, 2024 – May 1, 2025
Deployed a full-stack automated transit platform, integrating a Node.js-powered conversational WhatsApp bot with a relational SQLite database to manage real-time ride requests, dynamic manifests, and fleet operations. Developed responsive driver and passenger web dashboards featuring an interactive 10-seat vehicle grid, implementing strict real-time state management to handle concurrent users and completely prevent double-booking. Engineered a custom location-validation engine and master admin tracker, utilizing the Google Maps Geocoding API to dynamically snap user coordinates to official transit stops while visualizing live fleet occupancy and passenger demographics. Technologies used : Node.js, Express, SQLite, WhatsApp API, AWS, Caddy
Movie Intent Engine
January 1, 2024 – May 1, 2025
Fine-tuned a Transformer architecture (bert-base-uncased) using PyTorch and CUDA to perform deep semantic intent classification on a 50,000-record IMDB dataset. Monitored and mitigated model overfitting by tracking training loss against validation accuracy, ultimately achieving a high-confidence classification threshold for complex semantics. Implemented sub-word tokenization using Hugging Face's BertTokenizer, optimizing tensor padding and truncation to a max sequence length of 256 for optimal GPU memory utilization. Evaluated model performance using Scikit-Learn classification reports, confusion matrices, and ROC-AUC metrics, successfully mapping complex linguistic edge cases like double-negatives and sarcasm.
View ProjectCompetitive coding: 1500+ Peak Rating
CodeChef
June 1, 2026 – Present
Python certificate
HackerRank
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects showcase a diverse skill set, ranging from deep learning (NLP) to full-stack web development with real-time features. This breadth of experience, coupled with a focus on AI/ML in their B.Tech, aligns well with an AI Engineer target role. The competitive coding achievement indicates a drive for excellence and continuous improvement, which are positive cultural indicators. The academic nature of all projects means real-world team collaboration and corporate environment experience are yet to be demonstrated.
Soft Skills & Operational Fit
The candidate's resume highlights a 'motivated' and 'eager to contribute' attitude, emphasizing collaboration and continuous learning. The project descriptions demonstrate an ability to tackle complex problems and implement robust solutions, suggesting a good operational fit for roles requiring independent problem-solving and attention to detail. However, without specific psychometric or English test scores, a deeper assessment of communication clarity, work attitude, stress handling, and team collaboration is limited.