About the job
We're seeking an experienced AI/ML Security Engineer to serve as both a hands-on technical expert and strategic business leader in securing our artificial intelligence and machine learning systems. This dual-function role requires someone who can dive deep into technical security challenges while effectively communicating risks, strategies, and solutions to cross-functional teams and executive leadership.
Responsibilities
Design and implement comprehensive security frameworks for AI/ML pipelines, from data ingestion through model deployment
Conduct security assessments of machine learning deployments, identifying vulnerabilities including adversarial attacks, data poisoning, and model inversion risks
Develop automated security testing and monitoring solutions for AI/ML systems at scale
Lead incident response for AI/ML security events, coordinating technical remediation and stakeholder communication
Establish secure MLOps practices, including secure model versioning, access controls, and audit trails
Collaborate with engineering teams to integrate security-by-design principles into AI/ML development workflows
Translate complex AI/ML security risks into business impact assessments for leadership and stakeholders
Develop and present security roadmaps that align with business objectives and product timelines
Lead cross-functional teams through security initiatives, fostering collaboration between engineering, legal, privacy, and product teams
Establish metrics and KPIs to measure AI/ML security posture and communicate progress to executives
Qualifications
Minimum
7+ years of experience in cybersecurity with 4+ years specifically in AI/ML security
Proven track record of leading both technical teams and cross-functional business initiatives
Deep understanding of machine learning security threats (adversarial ML, model stealing, data poisoning, etc.)
Experience with secure cloud architectures and containerization technologies (Kubernetes, Docker)
Strong background in at least two programming languages (Python, Swift, C++, or similar)
Experience with ML frameworks (TensorFlow, PyTorch, Core ML) from a security perspective
Demonstrated ability to communicate technical concepts to non-technical stakeholders
Experience with regulatory compliance in AI/ML contexts (GDPR, CCPA, AI governance frameworks)
Preferred
Advanced degree in Computer Science, Cybersecurity, or related technical field
Experience with differential privacy, federated learning, or other privacy-preserving ML techniques
Background in threat modeling and security architecture design
Familiarity with accessibility considerations in AI/ML systems