Senior AI/ML Engineer – Applied AI Lead

Sourced from davidkennedyrecruitment.teamtailor.com

Lead the productionisation of machine learning models, establishing robust MLOps practices and delivering AI use cases with measurable business impact. Work on client lifetime value, churn prediction, and fraud detection while mentoring team members and collaborating with cross-functional stakeholders.

• Design, develop, and productionise machine learning models across training, validation, deployment, monitoring, and retraining.
• Lead AI use cases including client lifetime value, churn prediction, and fraud or abuse detection.
• Build and establish robust MLOps practices, including deployment pipelines, CI/CD, environment promotion, and model lifecycle management.
• Implement model monitoring frameworks covering performance, data drift, data quality, and business impact.
• Establish retraining and escalation strategies for production models.
• Implement model explainability and transparency using SHAP, feature attribution, and other interpretability techniques.
• Define and enforce best practices around model governance, documentation, versioning, and auditability.
• Collaborate with Data Engineering on data pipelines, feature engineering, reproducibility, and scalable data foundations.