ABÜber Amine
AI & Machine Learning consultant specializing in designing and deploying end-to-end intelligent systems. With a Master's in Data Science from EPFL, I transform business challenges into high-performance, production-ready applications. My expertise spans custom computer vision pipelines, generative AI integrations, and full-stack development of LLM-powered tools. Let's build a solution that drives your business forward.
Englisch
Muttersprachlich oder zweisprachig
Französisch
Verhandlungssicher
Deutsch
Grundkenntnisse
Arabisch
Muttersprachlich oder zweisprachig
Vor Ort möglich
Lausanne (bis zu 50 km)
Projekt- und Berufserfahrung
- Swisscom Digital LabData Science Research InternHIGHTECHMärz 2025 - August 2025 (5 Monate)Lausanne, Switzerland• Built a Docker-containerized, parametric synthetic data generation engine using Python and Blender to automatically render scenes with pixel-accurate instance masks and depth maps accelerating data creation by 70%.• Designed an instance segmentation framework leveraging Segment Anything Model achieving 73.7% mIoU.• Conducted synthetic to real data transfer by fine-tuning on limited real frames, and analyzed failure modes to deliver a reproducible, modular perception stack.
- Maxon MotorData Science InternHIGHTECHSeptember 2024 - Februar 2025 (5 Monate)Zürich, Switzerland• Developed an LLM-powered, multi-agent chatbot using CrewAI and LangChain with a RAG architecture to recommend drive systems based on user requirements, achieving 85% accuracy.• Engineered a full-stack product configuration tool by developing a web scraping pipeline for data acquisition, building a Django backend with SQLite3 to manage the data and expose it via REST APIs, and creating the dynamic user interface with JavaScript.
- JE EPFLData Science ConsultantHIGHTECHJuni 2024 - September 2025 (1 Jahr und 3 Monate)Lausanne, Switzerland• Collaborated with a sports team to build a real-time equestrian tracking system using Python, OpenCV, and PyTorch, integrating detection models and a custom Kalman filter to achieve 96% accuracy at 30 FPS.• Orchestrated an end-to-end mobile activity classification system utilizing React Native, Python and scikit-learn minimizing on-device memory usage by 20% through careful optimization for streamlined real-time inference.• Buil a document classification and information extraction pipeline using OpenCV, scikit-learn, and OCR (Google Cloud Vision); achieved 97.6% accuracy on real-world structured documents.• Engineered a train demand forecasting model, leveraging Pandas for complex feature engineering, a constrained LightGBM to address price endogeneity, and Optuna for systematic hyperparameter tuning.
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Ausbildung und Abschlüsse
- MSc in Data Science and RoboticsÉcole Polytechnique Fédérale de Lausanne (EPFL)2025MSc in Data Science and Robotics
- BSc in Micro-engineeringÉcole Polytechnique Fédérale de Lausanne (EPFL)2022BSc in Micro-engineering