Syed Obaidullah Hassan Chishti Mathematics, C++, English
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I am an AI Engineer with experience in developing and optimizing machine learning models for various applications. Currently, I work at CureMD, where I design sentiment analysis models and build analytics dashboards using Apache Superset. Previously, I worked as a Software Trainee Engineer - AI, where I developed and optimized OCR models for medical reports, built APIs using Python Flask, and implemented message queueing using RabbitMQ.

Besides my technical skills, I also have experience in leadership and financial management. As the Founding President of IET On Campus ITU, I led a team of over 40 members and won three on-campus recognition awards. I also served as the Treasurer of IEEE ITU Student Branch, where I maintained financial accounts of the society.

Overall, I am a problem-solver with excellent analytical and communication skills. I am proficient in Python, SQLite, NumPy, and Linux, and have experience in deep learning and computer vision. I am open to new opportunities in the field of AI and would love to contribute my skills to exciting projects.

Subjects

  • Math Pre-KG, Nursery-Grade 12

  • Python Beginner-Expert

  • C++ Beginner-Intermediate

  • Machine learning Python Beginner-Intermediate

Experience

  • AI Engineer and Team Lead (Deep Learning Team) (Oct, 2023–Present) at CureMD, Lahore
    - Fine-tune LLMs (Llama, Falcon, Orca, Mistral) on medical guidelines to create a chatbot for medical specialists.
    - Use lang-chain to get context based text and to create chatbot with the ability to save memory.
  • Associate AI Engineer (Feb, 2023–Sep, 2023) at CureMD, Lahore
    - Developed and trained a Tone Sentiment Model using CNN and using MEL Frequency and Spectrograms as features to extract valuable client sentiment-related insights for the client services department. Achieved an impressive accuracy rate of 84% in sentiment classification, enabling effective analysis and understanding of client sentiments.
    - Designed Bert Text Sentiment Model with 92% accuracy, enhancing decision-making through impactful textual insights.
    - Employed advanced techniques such as KMeans Clustering and a RNN-based IVR removal model to perform accurate speaker diarization within audio recordings.
    - Spearheaded the development of a comprehensive Analytics Dashboard catering to client services and sales departments. Leveraging Apache Superset and Flask, the dashboard provided intuitive and real-time visualization of key metrics, empowering stakeholders to make informed strategic decisions.
    - Configured PostgreSQL and MongoDB on Linux, enabling data storage and seamless integration with Apache Superset for data visualization.
  • Software Trainee Engineer - AI (Aug, 2022–Jan, 2023) at CureMD, Lahore
    - Trained Optimal Character Recognition model with 73% accuracy to extract unstructured text from scanned medical reports using PaddleOCR
    - Develop, Train and Test AI models. Perform model optimization for faster inference time and reduced memory footprint using CNN, Linear Regression, and Decision Trees
    - Setup the RabbitMQ, a distributed message queueing system, and implemented the queues, and producers for publishing and consumers for utilizing the data
    - Setup the Nvidia CUDA drivers on Linux

Education

  • BS Electrical Engineering (Sep, 2018–Aug, 2022) from Information Technology University, Lahore–scored 3.60/4.00

Fee details

    Rs2,000–5,000/hour (US$7.18–17.94/hour)

    The fee depends on the course to teach and the class of the student.

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