Internship: Generative AI & Deepfake Detection

Internship: Generative AI & Deepfake Detection

Company: HOPn UG Location: Puchheim, Germany Work Model: Onsite Contract: Internship

About Us

HOPn UG is a cutting-edge company leveraging AI to verify documents, detect fraud, and ensure authenticity in invoices and images. We are seeking a passionate intern with practical experience in deepfake detection and generative AI to contribute to real-world AI projects focused on document verification and fraud prevention.

Why Join Us

• Work on real-world AI systems that combat fraud and document manipulation.
• Gain hands-on experience with Generative AI, computer vision, and cybersecurity applications.
• Receive mentorship from experienced AI and security professionals.
• Opportunity to contribute to innovative products with real business impact.
• Enjoy a flexible and collaborative work environment.

Key Responsibilities

• Develop and evaluate AI models to detect deepfakes and synthetic content in images, PDFs, and scanned documents.
• Analyze invoices and business documents for manipulation, forgery, or AI-generated alterations.
• Support the integration of AI-powered document verification solutions into production workflows.
• Research and implement state-of-the-art techniques in deepfake detection, document forensics, and generative AI.
• Assist in building proof-of-concepts and datasets for fraud detection and authenticity verification.

Requirements

• Currently pursuing a degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
• Strong proficiency in Python.
• Experience with machine learning frameworks such as TensorFlow or PyTorch.
• Mandatory: Hands-on experience in deepfake detection, synthetic media detection, or digital image/document forensics through academic projects, research, internships, competitions, or personal projects.
• Experience with image processing, computer vision, or OCR tools (e.g., OpenCV, Tesseract).
• Familiarity with Generative AI models and techniques.
• Understanding of document analysis, fraud detection, or cybersecurity concepts is a plus.
• Strong analytical and problem-solving skills.
• Self-motivated, curious, and eager to work on challenging AI problems.

Preferred Qualifications

• Experience with transformer-based vision models, multimodal AI, or document understanding models.
• Experience working with invoice extraction, document classification, or fraud detection systems.
• Contributions to AI research, open-source projects, or Kaggle competitions related to computer vision or deepfake detection.