• Define the roadmap for the internal ML platform and ML Ops, taking ownership of existing tools and selecting the right additions to meet business needs. • Lead a cross-functional team of ML Engineers and specialists to build robust CI/CD pipelines for machine learning. • Establish highly optimized automations for model development, ensuring consistency in feature stores, model versioning, and deployment strategies. • Optimize cloud infrastructure to handle massive datasets while maintaining a keen eye on compute costs and resource allocation. • Implement comprehensive monitoring for model drift, latency, and bias to ensure our models remain high-performing. • Act as the primary interface between Data Science teams, Emerging Technologies and Core Engineering to remove bottlenecks in production pipelines.