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Schedule Interview NowMy name is Bilal A. and I have over 1 years of experience in the tech industry. I specialize in the following technologies: Machine Learning, Machine Learning Model, Artificial Intelligence, Deep Learning, Data Science, etc.. I hold a degree in Bachelor of Engineering (BEng). Some of the notable projects I’ve worked on include: AI-Powered Speakers Profile Filtering Tool, 🧠 AI Review Analyzer, 🚀 AI-Powered Legal Q&A App for UK Planning Legislation (2024), Landing page website, Similar Job Reterival System., etc.. I am based in Bradford, United Kingdom. I've successfully completed 11 projects while developing at Softaims.
I value a collaborative environment where shared knowledge leads to superior outcomes. I actively mentor junior team members, conduct thorough quality reviews, and champion engineering best practices across the team. I believe that the quality of the final product is a direct reflection of the team's cohesion and skill.
My experience at Softaims has refined my ability to effectively communicate complex technical concepts to non-technical stakeholders, ensuring project alignment from the outset. I am a strong believer in transparent processes and iterative delivery.
My main objective is to foster a culture of quality and accountability. I am motivated to contribute my expertise to projects that require not just technical skill, but also strong organizational and leadership abilities to succeed.
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Graphcore
This project involves creating an automated tool to filter your dataset according to your specific business rules. The deliverable goes beyond a simple filtered list. Key Deliverables: Filtered Dataset: An output file (Excel/CSV) containing only the rows that meet your defined criteria. AI-Powered Reasoning: A new column, "Reason," will be appended to every row in the output. Using AI, this column will automatically generate a concise natural language explanation stating why that particular row was included.
🧠 Built an AI-powered review analyzer using LangGraph, Pydantic & Streamlit 📊 Detects sentiment and diagnoses tone, urgency, and issue type from reviews 🤖 Generates smart, human-like responses for both positive and negative feedback 💻 Packaged in a clean, interactive Streamlit UI for easy use
🏛️ Automated Data Collection: Scraped and processed official UK planning legislation from (legislation.gov.uk) to build a reliable legal dataset. 🤖 Intelligent Q&A System: Developed a Retrieval-Augmented Generation (RAG) pipeline using Python, Streamlit, HuggingFace, and FAISS to answer user questions with context-aware, accurate responses. 💻 User-Friendly Web App: Delivered an interactive Streamlit interface where users can ask questions and instantly get answers sourced from real legal documents.
🌐 Landing Page Website Development with Flask Frontend Design: Built a responsive and modern landing page using HTML, CSS, and JavaScript to ensure a smooth user experience. Flask Backend Integration: Implemented Flask for backend logic, routing, and form handling to make the site dynamic and functional. Client-Ready Deployment: Delivered a clean, professional website fully ready for deployment and easy client-side updates.
I developed a powerful job retrieval system that takes user queries and finds the most relevant jobs by combining keyword matching and semantic search techniques. Using state-of-the-art embeddings and vector search (FAISS), the system understands context and retrieves job listings similar in meaning—not just keywords. This hybrid approach ensures users get accurate, context-aware job recommendations tailored to their query.
Bachelor of Engineering (BEng) in Mechanical engineering
2019-01-01-2023-01-01