AIML Security Engineering

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.

We offer- Opportunity to shape AI/ML security strategy at global scale Collaborative environment that values diverse perspectives and inclusive leadership Professional development budget for conferences, training, and certifications Comprehensive benefits including mental health support and accessibility accommodations 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 Business u0026 Strategic Leadership 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 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 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)