Mohammed Yasin
Senior Machine Learning Engineer at Ultralytics
Selangor, Malaysia
Summary
🤩
Rockstar🎓
Top SchoolMohammed Yasin is a Senior Machine Learning Engineer based in Selangor, Malaysia, with eight years of experience specializing in computer vision and production-ready ML systems. He has deep practical expertise optimizing inference pipelines and multi-GPU deployments—work that enabled real-time analytics across hundreds of streams and solved critical stability and throughput bottlenecks. At Ultralytics he progressed from community moderator to senior engineer, contributing 147+ PRs and key fixes to the widely used Ultralytics YOLO repository, improving training, export (ONNX, TensorRT, TFLite, CoreML) and validation for detection, segmentation and keypoint models. Comfortable working without GPUs, he builds efficient architectures and batching strategies that squeeze high FPS from constrained hardware. He pairs hands-on engineering with community-driven troubleshooting, having answered thousands of issues across GitHub and forums to improve user experience. Currently pursuing MPhil research in Computer Science, he brings both academic curiosity and production discipline to challenging CV problems.
9 years of coding experience
2 years of employment as a software developer
Master of Philosophy Computer Science, Master of Philosophy Computer Science at Universiti Teknologi MalaysiaBachelor of Computer Science Data Science and Computational Intelligence, Bachelor of Computer Science Data Science and Computational Intelligence at International Islamic University Malaysia
Github Skills (13)
computer-vision10
pytorch10
deeplearning-ai10
machine-learning10
exports10
data-export10
deep-learning10
python10
exporter10
onnx9
tflite8
tensorrt8
coreml8
Programming languages (15)
Github contributions (5)
ultralytics/ultralytics
Aug 2023 - Jul 2026
Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Role in this project:
ML Engineer
ML EngineerContributions:85 reviews, 321 PRs, 716 pushes in 2 years 11 months
Contributions summary:Mohammed contributed significantly to the development and maintenance of the Ultralytics YOLO repository, focusing on improvements related to model training, export, and validation. Their work included addressing bugs in the export process for various formats (ONNX, TensorRT, TFLite, CoreML) and fixing issues related to dynamic batch sizes and NMS. They also made modifications to segmentation, keypoint, and detection validation metrics, and incorporated improvements for the handling of YOLO-NAS models.
image-classificationinstance-segmentationobject-detectionobject-trackingpose-estimation
Y-T-G/ultralytics
Mar 2024 - Jul 2026
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
Contributions:4 PRs, 190 pushes, 79 branches in 2 years 4 months
coremlonnxopenvinopytorchtflite
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