Junior Embedded AI Platform Security Engineer (m/f/d)
NXP Semiconductors
Junior Embedded AI Platform Security Engineer (m/f/d)
Job Description
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, ORHave 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.More information about NXP in Belgium...#LI-b6c8
Locations
- Leuven
- Gratkorn
- Glasgow
Skills Required
- Computer Scienceintermediate
- Machine Learningintermediate
- model protection techniquesintermediate
- adversarial ML attacksintermediate
- privacy-preserving ML conceptsintermediate
Required Qualifications
- Have a background in Computer Science, Cybersecurity, or Cryptography and a strong interest in applied ML, OR (experience)
- Have a background in Machine Learning and an interest in cybersecurity. (experience)
- Knowledge of model protection techniques and IP security. (experience)
- Familiarity with adversarial ML attacks and defenses. (experience)
- Understanding of TEEs and secure enclaves. (experience)
- Knowledge of privacy-preserving ML concepts (differential privacy, federated learning basics). (experience)
- Awareness of regulatory frameworks for AI security and privacy. (experience)
- Have a background in Computer Science, Cybersecurity, or Cryptography and a strong interest in applied ML, OR (experience)
- Have a background in Machine Learning and an interest in cybersecurity. (experience)
- Knowledge of model protection techniques and IP security. (experience)
- Familiarity with adversarial ML attacks and defenses. (experience)
- Understanding of TEEs and secure enclaves. (experience)
- Knowledge of privacy-preserving ML concepts (differential privacy, federated learning basics). (experience)
- Awareness of regulatory frameworks for AI security and privacy. (experience)
- 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. (certification)
- More information about NXP in Belgium... (experience)
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).
- 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).
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