ML Engineer - AI Governance

Responsibilities

• Implement AI governance requirements across the ML lifecycle by embedding controls into engineering workflows and delivery practices.
• Build and maintain technical guardrails, monitoring, and governance tooling to support responsible, scalable AI deployment.
• Define and apply technical standards, documentation requirements, and deployment controls for governed AI delivery.
• Develop automation, APIs, and workflows to streamline compliance checks, traceability, audit support, and governance operations.
• Strengthen observability, validation, and reporting across AI systems, including models, prompts, responses, tool usage, and end-to-end AI activity.
• Partner with data science, product, legal, security, and other stakeholders to ensure AI solutions are implemented responsibly and aligned with governance expectations.
• Support AI security framework alignment, technical risk mitigation, and governance-by-design adoption across engineering teams.
• Contribute to governed MLOps implementation, including CI/CD integration, model versioning, reproducibility, and operational monitoring.
• Key Skills Required;
• Strong Python programming and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience building and deploying ML models and pipelines in production environments.
• Hands-on knowledge of MLOps, CI/CD, model versioning, reproducibility, and operational monitoring.
• Experience with APIs, automation tools, and engineering accelerators.
• Understanding of AI governance, responsible AI, fairness, observability, traceability, and auditability concepts.
• Familiarity with AI security controls, technical guardrails, and risk mitigation practices.
• Experience with cloud platforms such as AWS, Azure, or GCP, and containerization technologies such as Docker and Kubernetes.
• Strong communication and collaboration skills, with the ability to work effectively across technical and non-technical teams
• Experience and Qualifications:
• Bachelor's degree in Computer Science, Information Management, or a related field.
• Ideally 0-5+ years of experience in machine learning engineering, with a focus on responsible AI development and deployment.
• Experience in regulated industries is a plus.
• Fluency in English and local language required.

Additional Information

Role Summary As an ML Engineer - AI Governance, you will help implement and operationalize Nielsen's AI Governance framework across the ML lifecycle. You will work on technical guardrails, governance tooling, monitoring, automation, and deployment controls that help ensure AI systems are developed and deployed responsibly, consistently, and at scale.

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Company Intel

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