Join our Innovation Team, where we explore cutting-edge concepts at the intersection of Machine Learning and Security. Our mission is to develop forward-looking solutions—such as model protection, privacy-preserving ML, security for agentic AI, and anomaly detection—that will later be integrated into our Edge products. This requires high-level innovation skills combined with a hands-on mindset.
If you are passionate about building secure AI systems, exploring new ideas, and turning concepts into prototypes, this role is for you:
Define strategies and implement solutions for protecting ML models and sensitive data during deployment. Focus areas include IP protection, privacy-preserving inference, and resilience against adversarial manipulation.
Responsibilities:
- 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).
Required Skills:
- Have a background in Computer Science, Cybersecurity, or Cryptography and a strong interest in applied ML, OR
- Have a background in Machine Learning and an interest in cybersecurity.
- Knowledge 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.
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