Hey, I'm Oussema Ben Ameur.

2nd-year Applied Computer Science Engineering student at The National Engineering School of Sousse. I enjoy building things across the full software spectrum, with a growing focus on machine learning & data science.

~ / gnar
gnar@oba:~$ now
CurrentlySoftware Engineer · Part-time · Core Techs Solutions, Inc.Working across data science, machine learning, and software engineering — from building and shipping features to training models and making sense of data.
01 — About

What I'm into

A short list, in my own words. Not a mission statement.

  • Machine learning — model building, experimentation, and understanding the math underneath.
  • Data science — wrangling messy data into something meaningful.
  • Software in general — I'll try almost anything once.
Currently working on
Java–C++ interoperability for OCR systems
Currently exploring
Scientific ML and high-performance computing
02 — Work

Where I'm shipping

Part-time, in the thick of it. Document intelligence and computer vision at Core Techs Solutions.

  1. Part-time
    Part-Time Software Engineer
    Core Techs Solutions
    September 2025 — Present · Sousse, Tunisia
    • Built an end-to-end document extraction pipeline combining PaddleOCR, LayoutLM, and Qwen-VL with a RAG system for intelligent document querying.
    • Engineered a C++ inference layer with Java FFM bindings to run PaddleOCR and LayoutLM natively in the JVM, eliminating Python dependency overhead.
    • Built and refined deep learning models in PyTorch for production computer vision applications.
    • Shipped features across mobile (Flutter) and backend (Spring Boot) services for company products.
  2. Internship
    Software Engineering Intern
    Core Techs Solutions
    June 2025 — July 2025 · Sousse, Tunisia
    • Designed and trained a computer vision model to assess physical document condition — detecting folds, tears, and degradation for automated quality control.
    • Built data preprocessing and feature extraction pipelines in PyTorch, improving model accuracy over baseline.
03 — Projects

Things I've built or broken

A few that taught me something worth keeping.

FallahTech RAG

2025

Problem. A question-answering assistant over a fictional investment data room — it grounds every answer in retrieved documents and refuses to answer anything outside its corpus.

What I took away. Hybrid retrieval (semantic + BM25) pulls its weight, and confidence gating is the difference between a useful RAG and a confident liar.

  • Python
  • LangChain
  • Chroma
  • Groq
  • BM25
  • n8n

AI-Powered Writing Assistant

January 2025

Problem. Drafting emails and meeting summaries from rough bullet points, turning them into something readable without losing the writer's tone.

What I took away. Fine-tuning an LLM on business communication data, and the gap between raw model output and something a real person would send.

  • Spring Boot
  • React
  • Flutter
  • Fine-tuned LLM

Soil Nutrient Prediction

June 2024

Problem. Predicting essential soil nutrients to help optimize maize yields on African farms.

What I took away. How to pull signal out of environmental and satellite data (Sentinel, MODIS), and how much a good time-series feature matters.

  • Python
  • Time-series
  • Remote sensing

Book Status Assessement

2025

Problem. Assessing the physical condition of used books manually is subjective, time-consuming, and inconsistent, especially at scale for resale platforms or libraries.

What I took away. Applied computer vision to real-world data, handled noisy and imbalanced datasets, optimized model performance through hyperparameter tuning and deployment formats (ONNX, TensorRT), and gained experience in data preprocessing and evaluation.

  • Pytorch
  • Optuna
  • Python
  • NumPy
  • Pandas
  • Matplotlib
  • FastAPI

Play Store Market Analysis

December 2024

Problem. Predicting install counts across a 3M-row dataset of Play Store apps, and prototyping a market-research tool for indie developers.

What I took away. Handling scale with pandas and Keras without the notebook falling over, and how much cleaning matters before the model sees anything.

  • Keras
  • pandas
  • NumPy
  • Matplotlib
04 — Credentials

Certificates

05 — Contact

Find me

If something here sparked a question, reach out. I answer.