Job Description

Company overview:

HTech is a technology company based at Berytech Mathaf. We specialize in web development, AI development, management systems, and app development. We've worked on complex projects with both startups and large organizations. Some of our clients are the Ministry of Tech and AI, the Lebanese Army and many others.

Location: Berytech Mathaf

Website: https://www.htechco.com/

Internship overview:

This internship emphasizes mentorship, skill-building, and contributing to meaningful AI-driven solutions in a collaborative environment.

Duties and Responsibilities:

• Data Preparation & Cleaning: Assist in gathering, organizing, and preparing datasets for training and testing ML models.
• Model Training Support: Help in training small-scale ML/NLP models under the guidance of senior engineers.
• Experimentation & Research: Conduct literature reviews and experiment with open-source ML frameworks (e.g., Hugging Face, TensorFlow, PyTorch).
• Evaluation & Reporting: Run evaluation metrics, document results, and present findings to the team.
• Prototype Development: Contribute to building and testing proof-of-concept AI applications.
• Collaboration: Work closely with engineers to understand how ML models are deployed into production systems.
• Continuous Learning: Stay updated on the latest AI/ML trends and actively share insights with the team.

Learning Outcomes:

By the end of the internship, interns will:

• Gain practical experience with ML workflows (data, models, evaluation).
• Understand the basics of LLM fine-tuning and domain adaptation.
• Become familiar with industry-standard tools like Hugging Face Transformers and TensorFlow/PyTorch.
• Develop problem-solving and teamwork skills in a professional AI environment.

Majors preferences: Computer Science, Computer Engineering

Must-Have (Foundational Skills)

• Programming Basics: Familiarity with Python (comfortable writing scripts, working with libraries).
• Math/Stats Fundamentals: Basic understanding of linear algebra, probability, and statistics.
• ML Basics: Intro-level knowledge of machine learning concepts (e.g., supervised vs unsupervised learning, training/testing split)
• Libraries: Exposure to NumPy, Pandas, and at least one ML framework (Scikit-learn, TensorFlow, or PyTorch — even through coursework or personal projects).
• Version Control: Basic understanding of Git/GitHub.

Nice-to-Have (Bonus Skills)

• Experience with NLP libraries like Hugging Face Transformers.
• Knowledge of data preprocessing techniques (tokenization, embeddings).
• Familiarity with Jupyter Notebooks or Colab for experimentation.
• Previous course projects, Kaggle competitions, or personal ML projects.
• Eagerness to learn and explore new tools/technologies.
• Ability to work collaboratively and take feedback.

Company Profile