Job
Description
As a Senior AI/ML Engineer for Cybersecurity at NielsenIQ, you will play a crucial role in evolving the enterprise Identity and Access ecosystem by incorporating AI and machine learning to enhance security posture automation and user experience at scale. Your responsibilities will include designing, building, and operationalizing machine learning systems in complex distributed and cloud-based environments. **Role Overview:** In this role, you will lead the development of AI-driven identity access and security intelligence solutions, collaborating closely with Cybersecurity Engineering and AI teams. You will be tasked with designing ML architectures, constructing production-grade pipelines, deploying models at scale, and driving measurable outcomes through applied AI to support the Identity Security initiative. This position offers significant technical ownership and architectural influence in a hands-on Senior Engineering capacity. **Key Responsibilities:** - Lead the design and evolution of the IAM technology stack, ensuring adherence to top-tier security practices. - Design, build, and evolve AI/ML solutions for analyzing identity access and behavioral data to detect anomalies and automate identity security services. - Architect and implement scalable ML pipelines using Python, cloud-native services, APIs, and infrastructure-as-code. - Collaborate with Cybersecurity and Engineering teams to integrate ML models into enterprise IAM workflows and drive enterprise-scale adoption. - Apply advanced security engineering principles to develop and support complex software solutions and infrastructure upgrades. - Mentor junior engineers and help establish Cybersecurity engineering standards for applied AI. **Qualifications Required:** - Bachelor's degree in Cybersecurity, Computer Science, Computer Information Systems, Data Science, or a related field (Masters preferred). - 8 years of software engineering experience with 5 years focused on architecting AI/ML systems at a global scale. - Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn). - Hands-on experience with data pipelines, APIs, and distributed systems. - Knowledge of IAM capabilities, authentication/authorization, privileged access methodologies, and Zero Trust principles. - Experience deploying and operating ML models in cloud environments (Azure, AWS, GCP). - Familiarity with MLOps practices, REST APIs, Git workflows, containerization, and infrastructure-as-code. - Strong analytical thinking, problem-solving skills, and communication abilities. At NielsenIQ, you can enjoy a flexible and rewarding work environment, wellness plans, financial wellness tools, and career development opportunities. Additionally, the company's commitment to Diversity, Equity, and Inclusion ensures an inclusive workplace that embraces diverse perspectives. As a Senior AI/ML Engineer for Cybersecurity at NielsenIQ, you will play a crucial role in evolving the enterprise Identity and Access ecosystem by incorporating AI and machine learning to enhance security posture automation and user experience at scale. Your responsibilities will include designing, building, and operationalizing machine learning systems in complex distributed and cloud-based environments. **Role Overview:** In this role, you will lead the development of AI-driven identity access and security intelligence solutions, collaborating closely with Cybersecurity Engineering and AI teams. You will be tasked with designing ML architectures, constructing production-grade pipelines, deploying models at scale, and driving measurable outcomes through applied AI to support the Identity Security initiative. This position offers significant technical ownership and architectural influence in a hands-on Senior Engineering capacity. **Key Responsibilities:** - Lead the design and evolution of the IAM technology stack, ensuring adherence to top-tier security practices. - Design, build, and evolve AI/ML solutions for analyzing identity access and behavioral data to detect anomalies and automate identity security services. - Architect and implement scalable ML pipelines using Python, cloud-native services, APIs, and infrastructure-as-code. - Collaborate with Cybersecurity and Engineering teams to integrate ML models into enterprise IAM workflows and drive enterprise-scale adoption. - Apply advanced security engineering principles to develop and support complex software solutions and infrastructure upgrades. - Mentor junior engineers and help establish Cybersecurity engineering standards for applied AI. **Qualifications Required:** - Bachelor's degree in Cybersecurity, Computer Science, Computer Information Systems, Data Science, or a related field (Masters preferred). - 8 years of software engineering experience with 5 years focused on architecting AI/ML systems at a global scale. - Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow,
