Open to opportunities

Mostafa Mohsen

@mostafamohsen

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Experienced Computer Vision Engineer with a focus on AI and ML.

Canada

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What I'm looking for

I am looking for a challenging role in AI and machine learning that fosters innovation and growth.

I am a passionate Computer Vision Engineer with extensive experience in developing real-time perception systems for self-driving technology. At Pilotier, I led the development of a perception stack that achieved state-of-the-art metrics in optical flow, showcasing my ability to innovate under pressure and deliver high-quality results.

My academic background includes a Bachelor of Engineering in Software Engineering from McMaster University, where I excelled in courses such as Software Design and Deep Learning. I have also completed a Deep Learning Specialization by Andrew Ng, further enhancing my expertise in machine learning and computer vision.

Throughout my career, I have been recognized as a Multi-Hackathon Winner and have contributed to various projects, including optimizing models for IBM and developing algorithms for self-driving vehicles. I am eager to leverage my skills in a senior-level role that challenges me and allows for professional growth.

Experience

Work history, roles, and key accomplishments

Computer Vision & ML Engineer - Self Driving

Pilotier

May 2022 - Present (3 years)

Led the development of Pilotier's real-time perception stack, achieving state-of-the-art metrics on optical flow. Designed a condensed 3D detection world representation algorithm and created a novel SceneFlow method under hard time constraints. Accelerated team productivity by developing a timing utility for the perception stack.

PyTorch OpenCV TensorRT CUDNN Git Computer Vision Deep Learning

Computer Vision Engineering Intern

Pilotier

May 2021 - Present (4 years)

Created a physical-based road segmentation algorithm running at 1 ms. Designed and programmed a self-driving perception stack leveraging depth, optical flow, semantic segmentation, and object detection.

OpenCV Object Detection Optical Flow

Data Science Intern - Computer Vision

IBM

Jan 2021 - Present (4 years 4 months)

Conducted technical research on optimizing computer vision models using TensorRT, including Detectron, Yolov5, Mask R-CNN, EfficientNet, EfficientDet, and GoogLeNet. Developed a MEC (Multi-Access Edge Computing) scrum POC for model inference to measure MEC latency versus public cloud latency.

TensorRT Detectron EfficientDet GoogLeNet Computer Vision MEC YOLO V5

Enterprise Data Architect Intern - A.I. Platforms

TD Canada Trust

May 2020 - Present (5 years)

Outlined and documented a PySpark framework for job scheduling, monitoring, and integration. Detailed the ETL process, execution, and exception handling within the framework.

Pyspark ETL Scheduling Monitoring Integration

Education

Degrees, certifications, and relevant coursework

McMaster University

Bachelor of Engineering, Software Engineering

2017 - 2022

Grade: 3.7

Completed a Bachelor of Engineering in Software Engineering with a co-op option. Coursework included Software Design & Concurrency, Data Structures & Algorithms, Software Project Management, and Engineering Computation, achieving a GPA of 3.7.