Machine Learning Engineer with experience in computer vision, Python-based backend development, and ML model deployment. Worked on projects involving PyTorch, MLflow, Flask, AWS, Docker, GraphQL, Django, Kafka, and Sprin…
Machine Learning Engineer with experience in computer vision, Python-based backend development, and ML model deployment. Worked on projects involving PyTorch, MLflow, Flask, AWS, Docker, GraphQL, Django, Kafka, and Spring Boot across machine learning and software engineering roles.
Transformed vast amounts of data for different sports Ads and sponsor logos with Roboflow, leveraging transfer
learning, data analysis, and diverse data augmentation techniques to boost model performance by 15%
• Implemented hyperparameter tuning, experiment tracking and model registry using MLflow, ensuring
precise monitoring of production model drifts and wrapped the prediction service in Flask API, reducing latency
by an impressive 20%, deploying the model on AWS using docker
Engineered custom yolov5 models in PyTorch as a computer vision pipeline.
Transformed vast amounts of data for different sports Ads and sponsor logos with Roboflow.
Leveraged transfer learning, data analysis, and diverse data augmentation techniques to boost model performance by 15%.
Implemented hyperparameter tuning, experiment tracking and model registry using MLflow.
Ensured precise monitoring of production model drifts.
Wrapped the prediction service in Flask API.
Reduced latency by 20%.
Deployed the model on AWS using docker.
Pioneered a textual content delivery network, a MongoDB backed GraphQL application.
Seamlessly integrated real-time government regulation updates during COVID-19.
Achieved an average response time of 120ms.
Designed and deployed a standalone Python Django framework.
Facilitated quicker access to vital flight information.
Improved decision-making.
Provided an intuitive interface for pushing data to Kafka topic for other teams.
Reduced manual configuration errors by 75%.
Led the development of a python Flask-based Robotic Process Automation (RPA) bot automating the refund process of 500+ cancellation requests daily.
Saved 20 hours of manual effort for the support team.
Worked on Java expertise in Micro-service-based Architecture with REST APIs using the Spring Boot framework.
Streamlined the insurance process by developing a dedicated service.
Increased insurance sales by 30%.
Built a Ship Recognition System using TensorFlow Object Detection API.
Trained Faster-RCCN model with up to 99.5% accuracy in image classification and localization of different ships in a video feed.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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