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Faizan A. - Ml Engineer, React Native, nextjs

My name is Faizan A. and I have over 8 years years of experience in the tech industry. I specialize in the following technologies: Natural Language Processing, Model Optimization, Deep Learning, Computer Vision, Python, etc.. I hold a degree in Bachelor of Computer Science (BCompSc). Some of the notable projects I’ve worked on include: SmartComply, GoldenEye Data Processing, CheckMA - A cloud solution for students assignments and learning, Linkedin profile Selection based on Job Description using NLP. I am based in Islamabad, Pakistan. I've successfully completed 4 projects while developing at Softaims.

I thrive on project diversity, possessing the adaptability to seamlessly transition between different technical stacks, industries, and team structures. This wide-ranging experience allows me to bring unique perspectives and proven solutions from one domain to another, significantly enhancing the problem-solving process.

I quickly become proficient in new technologies as required, focusing on delivering immediate, high-quality value. At Softaims, I leverage this adaptability to ensure project continuity and success, regardless of the evolving technical landscape.

My work philosophy centers on being a resilient and resourceful team member. I prioritize finding pragmatic, scalable solutions that not only meet the current needs but also provide a flexible foundation for future development and changes.

Main technologies

  • Ml Engineer

    8 years

  • Natural Language Processing

    3 Years

  • Model Optimization

    7 Years

  • Deep Learning

    1 Year

Additional skills

Direct hire

Potentially possible

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Experience Highlights

SmartComply

Smart Comply is the compliance scheme founded in offering you unrivalled support, advice and value.

GoldenEye Data Processing

It is a files data processing application to process files and assign each file a category and sub categories using Data Processing and Machine Learning. We split data in these categories 1. Document Files 2. Document Images 3. Social Media 4. Person Images (Selfies, Group Photos) 5. Split Emojis and other

Linkedin profile Selection based on Job Description using NLP

Our goal for this project was to scrape people profile of specific skills from linkedin and train a Machine Learning model. So when we have a job description, we feed into model and get top profiles for that job description. We scrapped a number of profiles from linkedin. Then train a Deep Learning model using Tensorflow with our labeled data. After that we created an API so when we pass job description to model, it gives us profiles of top people with skills related to that job description.

Education

  • University of Agriculture, Faisalabad

    Bachelor of Computer Science (BCompSc) in Computer science

    2015-01-01-2019-01-01

Languages

  • English
  • Urdu

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