Mohamed Elgohary

I am a Junior Machine Learning Engineer with a strong foundation in Computer Science and advanced specialized training in Artificial Intelligence from the National Telecommunication Institute (NTI) and the Digital Egypt Builders Initiative (DEBI). My technical expertise spans the full AI lifecycle, from developing Deep Learning models using TensorFlow and PyTorch to deploying scalable solutions with Docker and CI/CD pipelines. I am passionate about bridging the gap between theoretical research and practical application, ensuring that complex algorithms translate into reliable, high-performance software.  
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My professional experience at Corelia and Huawei focused on optimizing AI systems for diverse sectors, including smart cities and healthcare. I have a proven track record of delivering high-accuracy results, demonstrated by projects such as a Sign Language Translator that achieved 98% accuracy and a Face Recognition system that won first place in a DEBI hackathon. I am also proficient in modern AI architectures, including Generative AI, RAG pipelines, and NLP, allowing me to build cutting-edge intelligent workflows.  
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With fluent English proficiency (IELTS Band 8) and a collaborative mindset, I excel at communicating complex technical concepts to both technical and non-technical stakeholders. I am dedicated to continuous learning and leveraging data-driven insights to solve real-world operational challenges, making me ready to make an immediate impact in innovative engineering environments.  

I have gained practical engineering experience as a Data Scientist and Machine Learning Engineer at Corelia and an AI Engineer at Huawei. At Corelia, I focused on translating research concepts into functional projects, leveraging Python and advanced ML techniques to fine-tune algorithms and optimize pipelines. Previously at Huawei, I contributed to the development of AI systems for smart cities and healthcare, where I was recognized for enhancing model performance through experimentation and communicating complex technical ideas to diverse teams. 

I hold a Bachelor of Science in Computer Science from October 6 University, graduating with a 3.31 GPA in 2020. I advanced my specialization through the Digital Egypt Builders Initiative (DEBI), earning a Professional Certificate in AI and Data Science in 2025, followed by an Advanced Professional Diploma in Artificial Intelligence from the National Telecommunication Institute (NTI) in 2026. This formal education is complemented by technical certifications, including the Huawei Certified ICT Associate in AI (HCIA-AI) and specialized coursework from Stanford University and DeepLearning.AI.