Abdelhamid Assadi
AI Engineer
BERLIN
Summary
Engineering student with international experience in AI projects and research. Worked on practical solutions in data analysis, automation, and problem-solving across different fields. Comfortable working in teams and adapting to new challenges. Looking to contribute to projects where technology supports real needs.
Overview
1
1
year of professional experience
4
4
Certification
Work History
Artificial Intelligence engineer
Räppe Smile
12.2024 - 07.2025
- Built automated data pipelines with LLM APIs and RAG.
- Generated medical sales datasets, stored in Amazon DocumentDB.
- Developed time series models in PyTorch and SageMaker.
- Improved forecasting accuracy by 1520% over baseline.
- Delivered production-ready code and optimized performance.
Artificial intelligence Engineering intern
APAIA Technology
06.2024 - 09.2024
- Built CTI-Bench to benchmark large language models :
- Optimized evaluation pipelines, cutting time by 12%.
- Automated CVE-to-CWE mapping with Python and deep learning.
- Created RAG pipelines with LangChain, saving 30% prep time.
- Applied NLP tasks for classification, search, and summaries.
Education
Master of Science - Informatics
04-2026
Master of Science - Artificial Intelligence
04-2026
Preengineering Cycle - Pre-engineering Studies
06-2022
Skills
Machine learning
Data science
Python programming
Time Series Forecasting
Statistical modeling
Computer Vision
Natural Language Processing (NLP)
Large Language Models (LLMs) & Transformers
Retrieval-Augmented Generation (RAG) & LangChain
AWS (SageMaker, DocumentDB)
Data Pipelines
Big data technologies
Projects
Real-time Garbage Detection System (GitHub Repository)
- Built real-time garbage detection system using YOLOv8 and PyTorch
- Collected and labeled 1,500+ images to improve dataset quality
- Achieved 0.76 mAP@50 for people detection in street photos
- Reduced inference time to 25ms per image for real-time use
- Planned dataset expansion and testing larger Transformer-based models
Movie Recommendation System (GitHub Repository)
- Built hybrid recommender with content-based and collaborative filtering
- Applied RAG concepts, improving recommendation coverage by ~12%
- Designed interface for new user preferences and returning user history
- Scaled system to e-commerce and education with 1M+ interactions
- Set up pipeline with evaluation, boosting accuracy by 9%
Certification
- AWS Certified Machine Learning Specialty
- Python Institute Certified Associate Python Programmer (PCAP)
- FreeCodeCamp Machine Learning with Python
LANGUAGES
ENGLISH Advanced B2 onset
FRENCH Advanced B2 , DELF
GERMAN Intermediate ÖSD A2 certified (currently B1 level)
ARABIC Native
Personal Information
Work Availability
monday
tuesday
wednesday
thursday
friday
saturday
sunday
morning
afternoon
evening
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Timeline
Artificial Intelligence engineer - Räppe Smile
12.2024 - 07.2025
Artificial intelligence Engineering intern - APAIA Technology
06.2024 - 09.2024
Hochschule Schmalkalden - Master of Science, Informatics
Tekup University - Master of Science, Artificial Intelligence
Prepatory Institute of Monastir - Preengineering Cycle, Pre-engineering Studies