ML Engineer - AI Governance

Responsibilities

• Implement AI governance requirements across the ML lifecycle by embedding controls into engineering workflows.
• Build and maintain technical guardrails, monitoring, and governance tooling to support responsible AI deployment.
• Develop automation, APIs, and workflows to streamline compliance checks, traceability, and audit support.
• Strengthen observability and reporting across AI systems, including models, prompts, and end-to-end activity.
• Partner with data science, product, legal, and security teams to ensure AI solutions align with governance expectations.
• Contribute to governed MLOps implementation, including CI/CD integration, model versioning, and reproducibility.

Requirements

• Bachelor's degree in Computer Science, Information Management, or a related field.
• Strong Python programming skills and experience with ML frameworks (TensorFlow, PyTorch, or scikit-learn).
• Hands-on experience with MLOps, CI/CD, model versioning, and operational monitoring.
• Understanding of AI governance, responsible AI, fairness, observability, and traceability concepts.
• Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).
• Experience building and deploying ML models and pipelines in production environments.

Preferred Qualifications

• 0-5+ years of experience in machine learning engineering with a focus on responsible AI.
• Experience working within regulated industries.
• Familiarity with AI security controls and technical risk mitigation practices.

About the Company

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content—wherever and whenever it’s consumed.