AI Engineer Specialized in Building Scalable LLM Applications
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Arpatech
Data Scientist
June 24, 2026 – Present
neat-portfolio
May 25, 2026 – Present
Personal portfolio with dual Engineer and Researcher profiles — built with React + Vite. Live at fahad-portfolio.vercel.app
View Projectai-learning-hub
August 27, 2025 – Present
This hub collects practical resources, projects, and learning paths to make learning AI less overwhelming and more hands on.
View ProjectSwapping-Activation-Function
August 1, 2025 – August 1, 2025
Swapping-Activation-Function — repository
View ProjectFunctional-Model-API
July 27, 2025 – July 27, 2025
Multi-output image prediction model using VGG16 and Functional API with custom regression and classification heads.
View ProjectMulti-Output-Model
July 26, 2025 – July 26, 2025
Predicts age and gender from facial images using a pre-trained VGG16 model with custom multi-output heads.
View ProjectTransfer-Learning
July 24, 2025 – July 24, 2025
This project applies transfer learning to classify images of cats and dogs using pre-trained convolutional neural networks. It demonstrates both feature extraction and fine-tuning techniques
View ProjectCat-vs-Dog-Classifier
July 23, 2025 – July 23, 2025
A CNN-based project to classify images as cat or dog, trained on the Kaggle Dogs vs. Cats dataset. Includes data augmentation, model training, performance tracking, and sample output visualization.
View ProjectLeNET-5-Architecture
July 23, 2025 – July 23, 2025
This repo implements the LeNet-5 architecture from scratch and trains it on the MNIST dataset for handwritten digit classification.
View ProjectPooling-Layers
July 23, 2025 – July 23, 2025
This repo demonstrates how different pooling layers (max, average) affect feature map size, information retention, and model performance in CNNs.
View ProjectPadding-and-Strides-in-CNN
July 22, 2025 – July 22, 2025
This repo explores the impact of padding and stride configurations in CNNs, focusing on feature extraction and spatial reduction.
View ProjectCultural Fit Analysis
The candidate's projects are primarily focused on deep learning and computer vision, which aligns with a Data Scientist role. However, the projects are all personal, and there is only one listed professional experience with no details, making it difficult to assess broader cultural fit or collaboration experience. The experience level of 0 is inconsistent with a current Data Scientist role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's experience level is listed as 0, but they have a current Data Scientist role, which is contradictory. No psychometric or English test scores are available.