Machine Learning Engineering Manager - AI

- Lead and mentor a team of engineers in developing AI-driven analytics for Copilot usage and quality metrics. - Oversee technical strategy for identifying trends, conducting cohort analyses, and implementing workflows that connect quantitative metrics with qualitative conversation insights. - Prototype and scale ML models for anomaly detection and predictive insights. - Ensure compliance and security regarding data management for telemetry, logs, and conversation datasets. - Collaborate with product managers, data scientists, and UX designers to outline the roadmap and deliver user-friendly, high-impact workflows. - Facilitate integration with existing platforms (Azure Data Bricks and other Microsoft internal systems) while ensuring reliability, scalability, and cost-effectiveness. - Exhibit solid expertise in machine learning systems, anomaly detection, and processing large data sets. - Transform machine learning solutions into standardized frameworks. - Independently develop efficient, readable, and extensible code and model pipelines. - Maintain a customer-centered approach by recognizing customer needs, validating their viewpoints, focusing on the broader context, and acting as a trusted advisor. - Actively engage with observability measures (metrics, tracing, logs) and model evaluation frameworks.