AI/ML Security Engineer
il y a 2 jours
Leveraging AI to enhance cybersecurity while protecting machine learning systems from adversarial threatsPosition OverviewWe are seeking an innovative AI/ML Security Engineer who combines deep knowledge of cybersecurity with experience in artificial intelligence and machine learning. This cross-disciplinary role focuses on two key areas: using AI/ML techniques to detect and respond to threats more effectively, and ensuring the security of AI models against adversarial attacks such as data poisoning, model inversion, and evasion techniques.You will collaborate across security operations, data science, and DevSecOps teams to operationalize intelligent threat detection and protect critical AI systems from emerging threats.Key ResponsibilitiesAI for CybersecurityDevelop and operationalize AI/ML models for anomaly detection , threat intelligence analysis , and automated incident responseAnalyze large volumes of log and telemetry data to detect patterns indicative of cyber threatsIntegrate ML-driven detection with SIEM, SOAR, and XDR platforms to improve automation and speed of responseSecuring AI/ML SystemsImplement controls to protect AI pipelines from manipulation, including input validation, data sanitization, and model monitoringIdentify and mitigate threats such as data poisoning , model inversion , adversarial examples , and membership inferenceEvaluate ML models for robustness, fairness, and explainability from a security perspectiveGovernance & CollaborationWork with data scientists and MLOps teams to embed security into the AI development lifecycleDocument AI system threat models and design risk mitigation strategiesStay updated on AI security research, adversarial ML techniques, and emerging regulatory considerationsRequired Qualifications6+ years experience in cybersecurity and/or applied machine learningStrong knowledge of cybersecurity principles , threat modeling, and security architectureHands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn ) and data pipelinesUnderstanding of adversarial ML concepts and experience applying mitigation strategiesProgramming proficiency in Python, and experience with data analysis librariesPreferred QualificationsAdvanced degree in Computer Science, Cybersecurity, Machine Learning, or related fieldSecurity certifications (e.g., CISSP, OSCP, or ML-specific credentials)Experience with ML model deployment in secure environments (e.g., MLOps, containerization)Familiarity with AI governance, ethics, and security standards (e.g., NIST AI RMF, ISO/IEC 23894)Contributions to AI security research, open-source tools, or community knowledge #J-18808-Ljbffr
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