Summary
Overview
Work History
Education
Skills
Projects
Certification
Timeline
Generic

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
3
3
Certifications
4
4
Languages

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

Hochschule Schmalkalden
Schmalkalden, Germany
04.2001 -

Master of Science - Artificial Intelligence

Tekup University
Tunisia
04.2001 -

Preengineering Cycle - Pre-engineering Studies

Prepatory Institute of Monastir
Monastir,Tunisia
04.2001 -

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

Timeline

Artificial Intelligence engineer

Räppe Smile
12.2024 - 07.2025

Artificial intelligence Engineering intern

APAIA Technology
06.2024 - 09.2024

Master of Science - Informatics

Hochschule Schmalkalden
04.2001 -

Master of Science - Artificial Intelligence

Tekup University
04.2001 -

Preengineering Cycle - Pre-engineering Studies

Prepatory Institute of Monastir
04.2001 -
Abdelhamid AssadiAi Engineer