Ali Yehia

Machine Learning Engineer

adgvvx@r.postjobfree.com

312-***-****

**** ****** **, ****** **

www.linkedin.com/in/ali-

sherif-yehia

EDUCATION

GERMAN UNIVERSITY IN CAIRO

Cairo, Egypt

BSc Mechatronics Engineering

June 2012

SKILLS

Machine Learning

Deep Learning

Python

AWS

Pandas

Numpy

Scikit-Learn

CERTIFICATIONS

Machine Learning Nanodegree

- From Udacity

Advanced Python Design

- From Valeo

Introduction to Machine Learning

- From Valeo

CAREER OBJECTIVE

I am a software engineer with over 5 years of experience. I have a passion for working with emergent technologies and have a great interest in working with AI and applying machine learning to real world problems. EXPERIENCE

SENIOR EMBEDDED SOFTWARE ENGINEER

Valeo, Cairo, Egypt/ Mar 2016 – Present

Successfully deployed three vision and camera system projects with GM, VW, and BAIC.

Developed, tested, and debugged many highly reusable Python scripts for continuous integration systems.

Achieved safety level ASIL B for safety critical features in latest GM project which were successfully designed, developed and implemented in appliance to ISO 26262

FULL STACK WEB DEVELOPER

Ripplemark, Cairo, Egypt/ Oct 2015 – Mar 2016

Designed and developed multiple full stack websites that ensured a user friendly experience while maintaining proper handling of high traffic

Worked closely with clients and collaborated with management to set time tables and ensure 100% on-time delivery of milestones

Wrote effective, scalable back-end Python components to improve responsiveness and overall performance

TECHNICAL SUPPORT ENGINEER

IBM, Cairo, Egypt/ Apr 2014-Jun 2015

Provided remote technical support and action plans to clients and IBM technical personnel

Studied and worked with multiple architectures of IBM System X servers PROJECTS

IDENTIFYING AND CRETING CUSTOMER SEGMENTS

Applied unsupervised machine learning clustering techniques to very large real life datasets as a technique to help businesses make informed marketing and product decisions and be able to use existing customers to identify potential ones.

Used a variety of data cleaning and wrangling techniques to ensure final output validity

IMAGE CLASSIFER PROJECT

Implemented an image classification application using deep learning to classify new images.

This project was done using PyTorch library. Final trained algorithm reached an accuracy of over 85% of correct classification

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