Abd Raouf Zerkhef
AI & Data Science Student / Software Developer
About
I'm a software developer specializing in backend systems and mobile applications, currently pursuing an engineering degree in Artificial Intelligence & Data Science.
With hands-on experience building production systems in Go (Gin) and mobile apps with Dart (Flutter), I focus on scalable APIs, high-performance platforms, and seamless user experiences.
Driven by curiosity and a passion for innovation, I'm actively building expertise in Generative AI—combining solid engineering fundamentals with cutting-edge AI to create impactful, intelligent solutions.
Tech Stack
Experience
RetailSpot - (Remote / Paris, France)
Backend Developer
♦ Achieved sub-100ms latency for real-time ad auctions by leveraging Go concurrency and high-performance in-memory caching.
♦ Enabled global DSP compatibility by integrating OpenRTB and Prebid.js protocols, expanding programmatic bidding capabilities.
♦ Optimized database performance and reduced load by 30% through strategic in-memory caching and MongoDB query refinement.
♦ Collaborating in Agile sprints to deliver backend features supporting data-driven shopper targeting and high-traffic events.
Maystro Delivery - (Algiers, Algeria)
Mobile Developer
♦ Increased warehouse processing speed by 25% by developing a specialized WMS module for Winrah PDA devices using Flutter.
♦ Reduced UI state errors by 40% by implementing the BLoC pattern for complex real-time task management and location updates.
♦ Streamlined inventory tracking via RESTful API integration for real-time item lookup and automated put-away workflows.
♦ Delivered production-ready features within a high-pressure 15-day sprint, including a reusable library of Flutter components.
Education
Engineer's Degree in Computer Science
♦ Specialization: AI & Data Science at Ecole Supérieure en Sciences et Technologies de l'Informatique (ESTIN).
♦ 4th-year student in a 5-year rigorous engineering program focused on large-scale software systems and advanced AI.
♦ Winner of the NASA Space Apps Challenge (2023), outperforming 50+ teams with a data-driven prototyping solution.
♦ Strong academic focus on Probability, Statistics, and Machine Learning modeling for real-world applications.