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Python Engineer with backend systems, REST API, and AI/ML experience
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Assessing your cultural and operational fit
Computer Science undergraduate (Batch 2027) with strong Python proficiency and hands-on experience building backend systems, REST APIs, and end-to-end ML/AI applications. Skilled in Django, Django REST Framework, PostgreSQL, JWT authentication, serializers, Postman API testing, and RESTful API design - directly aligned with Gravity Engineering's Python Internship requirements. Demonstrated ability to deliver production-quality Python code through internships and independent projects. Eager to contribute to Gravity ER's backend engineering and AI/consulting initiatives from day one.
CGC University, Mohali
B.Tech. · Computer Science & Engineering
August 1, 2023 – June 30, 2027
New Era Sen. Sec. School, Parol (HPBOSE)
Intermediate · Science Stream
N/A – May 31, 2023
New Era Sen. Sec. School, Parol (HPBOSE)
Matriculation
N/A – May 31, 2021
Sensation Software Solutions
Data Science Intern
June 1, 2025 – July 1, 2025
India
NeuralDocs - RAG-Based AI Content Assistant (Full-Stack)
June 4, 2026 – Present
Designed and implemented RESTful API endpoints using Django REST Framework (DRF), including serializers, viewsets, CRUD operations, JWT-based user authentication, and API versioning - directly matching Gravity ER's Python intern requirements. Integrated OpenAI embeddings with Pinecone vector store via LangChain LCEL; architected clean API layer with middleware-level error handling, request validation, and structured JSON response patterns. Deployed as a cloud-ready full-stack web application (Next.js 14 + TypeScript frontend, Python/DRF backend) - demonstrating full SDLC ownership from schema design to API deployment. Tested all API endpoints through Postman, writing test collections for CRUD flows, auth token refresh, and edge-case error handling.
Attention-Based Sentiment Analyzer
June 4, 2026 – Present
Built end-to-end Python NLP pipeline with Bidirectional LSTM and custom multi-head attention mechanism, achieving ~88% classification accuracy — 9% F1-score gain over TF-IDF baseline. Applied dropout regularization, learning rate scheduling, and early stopping; implemented attention heatmaps for model interpretability; deployed as an interactive Streamlit web application. Collaborated with cross-functional team under faculty mentor, simulating Agile sprint dynamics.
Diabetes Prediction - Deployed ML Web App
June 4, 2026 – Present
Logistic Regression classifier achieving ~92% accuracy (F1: 0.89) after hyperparameter tuning; deployed as a real-time interactive web application via Streamlit — demonstrating Python from model development to deployment. Implemented clean data pipelines: preprocessing, feature scaling, model serialization with pickle, and REST-style Streamlit API for user input handling.
Advanced Personality Development Certification
Bizgurukul Pvt. Ltd.
June 1, 2026 – Present
Introduction to Cybersecurity
Cisco Networking Academy
June 1, 2026 – Present
Data Science Training Certificate
Unknown
June 1, 2025 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from full-stack RAG systems to NLP and ML web apps, indicates a broad interest in modern technologies relevant to a Python Engineer role. Participation in hackathons and competitive programming suggests a drive for continuous learning and problem-solving. The volunteer and coordinator roles highlight leadership and teamwork potential. The alignment of project technologies (Django REST Framework, JWT auth) with typical industry requirements suggests a good fit for a fast-paced development environment.
Soft Skills & Operational Fit
The candidate demonstrates initiative through personal projects and participation in hackathons, suggesting a proactive work attitude. Collaboration skills are mentioned in the 'Attention-Based Sentiment Analyzer' project and leadership roles in activities. The competitive programming background indicates problem-solving abilities. However, without psychometric test results, a comprehensive assessment of stress handling and team collaboration is limited.