ML Model Security & Privacy Architect

• Design and implement model obfuscation and secure packaging techniques.
• Develop IP protection strategies.
• Enable secure execution environments for customer models using TEEs. * Assess and mitigate adversarial ML threats (evasion, poisoning attacks).
• Define privacy-preserving inference mechanisms (e.g., differential privacy). * Advise on compliance with AI security and privacy regulations (GDPR, EU AI Act).

• Degree in in Computer Science, Cybersecurity, or Cryptography and a strong interest in applied ML
• 5 years or more experience of model protection techniques and IP security.
• Familiarity with adversarial ML attacks and defenses.
• Understanding of TEEs and secure enclaves.
• Knowledge of privacy-preserving ML concepts (differential privacy, federated learning basics).
• Awareness of regulatory frameworks for AI security and privacy

Please note: The successful candidate may/will be responsible for security related tasks. The assignment may/will be in scope of security certifications, therefore a conscious and reliable way of working is necessary.