• Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies. • Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage. • Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations. • Accountable for design, development and maintenance of Models as Service • Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences. • Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams • Delivery of critical milestones for model deployment in the AWS and GCP clouds. • Adopt and promote MLOps best practices to the Data Science community. • Proactively monitor cloud usage to drive cost-saving opportunities across cloud accounts and deployed infrastructure.