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Jamal N. AI, Machine Learning and MLOps

My name is Jamal N. and I have over 3 years of experience in the tech industry. I specialize in the following technologies: Machine Learning Model, Deep Learning, Computer Vision, Natural Language Processing, Optical Character Recognition, etc.. I hold a degree in Bachelor of Computer Science (BCompSc). Some of the notable projects I've worked on include: 3D Point Cloud Classification, Brain Tumor Segmentation – U-net + EfficientNetB7, GPU-Accelerated Video OCR with PaddleOCR, Intelligent WhatsApp Chatbot with Human-AI Collaboration, Super Receptionist – AI-Powered Call Management for Businesses, etc.. I am based in Germantown, United States. I've successfully completed 20 projects while developing at Softaims.

I specialize in architecting and developing scalable, distributed systems that handle high demands and complex information flows. My focus is on building fault-tolerant infrastructure using modern cloud practices and modular patterns. I excel at diagnosing and resolving intricate concurrency and scaling issues across large platforms.

Collaboration is central to my success; I enjoy working with fellow technical experts and product managers to define clear technical roadmaps. This structured approach allows the team at Softaims to consistently deliver high-availability solutions that can easily adapt to exponential growth.

I maintain a proactive approach to security and performance, treating them as integral components of the design process, not as afterthoughts. My ultimate goal is to build the foundational technology that powers client success and innovation.

Main technologies

  • AI, Machine Learning and MLOps

    3 years

  • Machine Learning Model

    1 Year

  • Deep Learning

    2 Years

  • Computer Vision

    2 Years

Additional skills

Direct hire

Potentially possible

Previous Company

Self Employed

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Experience Highlights

3D Point Cloud Classification

This project focuses on classifying objects using 3D point cloud data, which represents real-world environments in 3D space using collections of points captured by LiDAR or depth cameras. It leverages

Brain Tumor Segmentation – U-net + EfficientNetB7

Developed a deep learning model for accurate brain tumor segmentation from MRI scans using U-Net with EfficientNetB7 encoder. Applied preprocessing (resizing, normalization, augmentation) and optimize

GPU-Accelerated Video OCR with PaddleOCR

I developed and tested a GPU-powered Optical Character Recognition (OCR) pipeline using PaddleOCR on Google Colab. The goal was to accelerate text extraction from recorded video files stored locally,

Intelligent WhatsApp Chatbot with Human-AI Collaboration

I built an advanced AI-powered WhatsApp chatbot designed to act like a human business executive. It handles customer inquiries, shares detailed information about services, and generates quotes instant

Super Receptionist – AI-Powered Call Management for Businesses

Businesses often miss calls outside business hours or when staff are occupied, leading to lost opportunities and a diminished brand image. Hiring full-time receptionists is costly, while traditional v

Education

  • Purdue University

    Bachelor of Computer Science (BCompSc) in Computer science

    1993-01-01-1997-01-01

Languages

  • English (Native or Bilingual)
  • Russian (Conversational)