AI & Machine Learning Internship

Praktix is a next-generation education platform redefining how talent is developed by bridging the gap between academia and real-world industry.

Operating at the intersection of education, industry, and practical execution, Praktix delivers structured, outcome-driven programs designed to prepare students and professionals for actual career demands — not just theoretical knowledge.

Through internships, mentorship, and hands‑on projects led by global industry experts, Praktix empowers learners to build real portfolios, gain practical experience, and transition seamlessly into the workforce. By connecting universities, companies, and professionals on a single platform, Praktix creates an ecosystem where learning translates directly into measurable career outcomes.

Are you ready to move beyond theory and build real‑world AI solutions?

Praktix offers a hands‑on AI & Machine Learning Internship (3 Months) designed to give students and recent graduates real‑world experience in artificial intelligence, machine learning models, and data‑driven applications.

Developed in collaboration with industry experts in Germany, this program focuses on practical implementation, real datasets, and structured mentorship — ensuring participants build measurable outcomes and industry‑relevant skills.

Tasks

As an AI & Machine Learning Intern, you will:

• Work on real‑world AI challenges, collaborate in structured teams, and build machine learning models that simulate real industry workflows.
• Gain hands‑on experience in developing intelligent systems, working with real datasets, and applying AI tools used in modern companies.
• Build strong technical confidence, develop a portfolio of AI‑based projects, and prepare for future roles in data science, machine learning, and AI engineering.

Requirements

• Basic understanding of Python programming
• Familiarity with data analysis concepts
• Interest in Machine Learning and Artificial Intelligence
• Basic knowledge of libraries such as Pandas, NumPy, or Scikit‑learn is a plus
• Understanding of statistics fundamentals is an advantage

• English Level: B2 or higher
• Strong willingness to learn and explore new technologies
• Problem‑solving mindset
• Ability to work independently and collaboratively
• Good communication and time‑management skills

Benefits

• Machine Learning fundamentals and model building
• Data preprocessing and feature engineering
• Model evaluation and performance improvement
• Working with real‑world datasets
• AI workflow development
• Portfolio project development aligned with industry standards