Saife Shuhaib Md.

I'm Saife Shuhaib, a Software Engineer who bridges the gap between cutting-edge AI and robust backend engineering. I specialize in building intelligent, scalable systems—from legal AI assistants and transcription platforms to advanced image processing tools—that transform complex challenges into streamlined solutions. With deep expertise in Python, Django, and AI frameworks like PyTorch and OpenCV, I focus on integrating machine learning into backend infrastructures to drive real-world impact. Whether it's reducing system latency by over 60%, automating workflows, or boosting user satisfaction through thoughtful architecture, I engineer systems that are not only technically sound but strategically aligned with business outcomes. Passionate about clarity, precision, and performance, I thrive on building meaningful technology that delivers measurable value.

Key Contributions

• Designed the system for processing text data and storing it in a vector database.
• Developed a module to retrieve state-specific legal data from the vector database.
• Designed a logging system for the scraper used to extract legal data.
• Optimized vector query accuracy through data cleaning and query augmentation.
• Improved citation module accuracy by 60%.
• Implemented multithreading for parallel execution of independent API calls within the system.
• Reduced overall system response time from 1.5 minutes to 30 seconds, a 67% reduction.

• Python
• Django
• PostgreSQL
• AWS (RDS, EC2)
• Supabase
• FAISS
• Docker

Key Contributions

• Implemented meeting transcription versioning and tagging systems.
• Designed APIs for generating various file notes from user transcripts.
• Migrated all database tables and data from the dev environment to production using pg_dump.
• Helped transition from session-based user settings to fetching them from the database.
• Increased user satisfaction by 80% and eliminated manual data entry at each login.
• Created APIs for letting admin modify system prompts from the front-end.
• Increased admin productivity and completely eliminated developer dependency for prompt modifications.

• JavaScript
• Express
• Knex.js
• PostgreSQL
• AWS (RDS, EC2)
• Docker
• Assembly AI

Key Contributions

• Developed a module to detect comic book panels and speech/thought bubbles.
• Trained an object detection model to identify object areas and extract polygon coordinates.
• Conducted project time estimation, resource planning, and resource allocation.
• Implemented preprocessing techniques for comic book images to enhance detection accuracy.
• Optimized model performance for inference and deployment.
• Reduced translation error by 25%.

• Python
• PyTorch
• YOLOv8
• OpenCV
• ONNX Runtime
• Roboflow

Key Contributions

• Created model loaders and converted models to OpenVINO format for edge device inference.
• Packaged emotion and landmark detection models into DLL files for seamless integration with desktop apps.
• Applied multithreading techniques to improve processing efficiency and speed.
• Implemented frame-skipping to reduce computational load while maintaining accuracy.
• Ensured the solution provided real-time analysis within the constraints of edge device hardware.
• Improved performance by 40% through multithreading and frame skipping.

• C++
• OpenVINO
• OpenCV

Key Contributions

• Developed a system to securely store face embeddings.
• Implemented homomorphic encryption using Microsoft SEAL to perform secure recognition on encrypted data.
• Integrated the encryption module with an Android app using Java Native Interface.
• Optimized encryption settings to minimize file size and decryption time.
• Achieved 90% file size reduction (to 30 KB) with inference times under 1 second.

• C++
• Java
• Microsoft SEAL
• OpenCV
• Dlib

Key Contributions

• Developed an object detection model to identify changes in website elements.
• Created a module to analyze the DOM and model outputs to determine which elements were modified.
• Reduced manual QA efforts by 50%.

• Python
• JavaScript
• Selenium
• Bootstrap
• YoloV5
• HTML5
• CSS3

Key Contributions

• Developed a module that utilizes a layout-based OCR model to extract information from post orders.

• Python
• PDF Plumber
• OpenCV
• Nanonets

Chess-AI

Developed with Django, the python-chess library, and chessboard.js, this web-based chess application allows users to participate in chess matches against an AI opponent. The bots are developed using different algorithms, with one utilizing minimax and another employing a Convolutional Neural Network trained on a kaggle chess dataset.

• Python
• JavaScript
• Pytorch
• chessboard.js
• python-chess
• ONNX Runtime

Flashcards

A Django-based web application designed for efficient review of solved leetcode questions. Users can input the problem link, specify a topic for categorization, and provide their solutions. The application will automatically generate dedicated pages for each problem by utilizing GraphQL queries to the leetcode/graphql server for getting additional question information.

• Python
• JavaScript
• GraphQL
• Bootstrap