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Muneeb A. AI, Cloud and MLOps

My name is Muneeb A. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Computer Vision, Machine Learning, PyTorch, LangChain, AI Agent Development, etc.. I hold a degree in Bachelor of Computer Science (BCompSc). Some of the notable projects I’ve worked on include: Voice-Powered AI Tutor SaaS - VC Funded (£2M Funding), Vision LLM Powered Medical Diagnosis (VC Funded MVP), Document AI - Purchase Order Data Extraction, AI-Powered Login Security for Android Apps, Google Cloud Vision OCR, etc.. I am based in Lahore, Pakistan. I've successfully completed 6 projects while developing at Softaims.

I employ a methodical and structured approach to solution development, prioritizing deep domain understanding before execution. I excel at systems analysis, creating precise technical specifications, and ensuring that the final solution perfectly maps to the complex business logic it is meant to serve.

My tenure at Softaims has reinforced the importance of careful planning and risk mitigation. I am skilled at breaking down massive, ambiguous problems into manageable, iterative development tasks, ensuring consistent progress and predictable delivery schedules.

I strive for clarity and simplicity in both my technical outputs and my communication. I believe that the most powerful solutions are often the simplest ones, and I am committed to finding those elegant answers for our clients.

Main technologies

  • AI, Cloud and MLOps

    2 years

  • Computer Vision

    1 Year

  • Machine Learning

    1 Year

  • PyTorch

    1 Year

Additional skills

Direct hire

Potentially possible

Previous Company

Systems Limited

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Experience Highlights

Voice-Powered AI Tutor SaaS - VC Funded (£2M Funding)

🎤 As Lead ML Engineer, built MVP that secured £2M VC acquisition—voice-powered AI tutor using LangGraph & Semantic Kernel. 🤖 Solves complex STEM problems with real-time code & charts. 🔊 Engineered custom audio pipeline, cutting costs by 80%. ☁️ Scalable deployment on Fireworks AI, Azure & AWS. 💰 Fine-tuned LLaMA-3.2-12B to slash ops costs 50%. 🎓 Tracks student progress for personalized learning. 🚀 Led full dev cycle—AI, backend & DevOps—solo.

Vision LLM Powered Medical Diagnosis (VC Funded MVP)

Helped Build and Fine-Tune an MVP for Radiologics, a VC funded company working on automatic DDH diagnosis through AI. I helped fine-tune Microsoft's Phi-4 Vision LLM and YOLOv11 models for diagnosis and classification of patients affected from DDH. Currently this project is undergoing a regulatory testing phase, and has also been tested on real users providing a staggering 90+% accuracy.

Document AI - Purchase Order Data Extraction

I have designed a fully featured Document AI Extraction System for my customers, it is a fully automated system without the need for any Human in the Loop Intervention, it is trained on the State of the Art YOLOv8 and Detectron2 Models It features built-in LabelBox Integration for Annotations, and automatic training and deployment system. It also has built-in Microsoft Graph & Google Integrations, so you can get your Purchase Order's / Receipts Directly from your Outlook for Business and Upload the to Microsoft SharePoint in Converted Microsoft Excel Format.

AI-Powered Login Security for Android Apps

I was given the task to add an added Layer of Login Security to an Android App. As a Machine Learning Developer I devised a full end-to-end solution using the Firebase Admin SDK to get the login attempt information such as DeviceID, Login Location, Login Attempts, User Fingerprints & More and determine if the request was a legitimate request based on previously collected data. I used pyOd Library to implement a state of the art anomaly detection algorithm called "ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions", I implemented the following algorithm into my AI Solution for the customer, and the results were amazing. My customer was very satisfied with the results.

Google Cloud Vision OCR

I helped my clients design a system to perform OCR using the Google Cloud Vision OCR Service, which is hands-down the best OCR service with support for over 132 languages. Google Cloud Vision OCR only returns the results in form of JSON results and has no support for embedding the results on the PDF files, so I helped design this system.

Education

  • National University of Science and Technology

    Bachelor of Computer Science (BCompSc) in Computer engineering

    2014-01-01-2017-01-01

Languages

  • English
  • French

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