ML Platform Innovation Lead
2 months ago
- Lead the development and management of the Platform roadmap, working with senior colleagues across enterprise architecture, solution architecture, data and AI governance, engineering and data science, identifying gaps and opportunities for new tools and services to enrich the platform given new and emerging requirements
- Lead and prioritise the development of new and improved functionalities for our Data Science Platform(s).
- Own and promote the ‘inner-sourcing’ strategy to make the most of developments and innovations across the organisation
- Collaborate with Enterprise Architecture colleagues to explore, test and integrate relevant vendor or open-source capabilities.
- Report on progress and generation of value clearly and succinctly to a wide range of colleagues, in and outside the immediate team.
- Be a subject matter expert across BT for MLOps, with a responsibility for advising other teams to encourage the usage of the platform.
- Contribute to the development of and ensure adherence to relevant frameworks and regulations to ensure safe development of AI applications.
- Support business case development, tendering, budgeting and forecasting processes when required.
- Management, coaching and mentoring of DS Platform specialists.
What we are looking for from you…
- 5-7 years+ leading initiatives in MLOps / Data Science/Software engineering.
- Direct and recent experience of using cloud ML platforms such as Google Cloud Platform (GCP) Vertex AI, Amazon Web Services (AWS) Sagemaker or Microsoft Azure ML Studio.
- Prior experience building ML pipelines, productionising ML solutions, and building products and services to support this.
- Experience of working directly with customers/stakeholders and, potentially, as part of an Agile squad.
- Ability to prioritise competing demands and backlogs based on commercial drivers.
- Team management and coaching, mentoring and career development experience.
- Demonstration of thought leadership through significant contributions to the wider Data Science community.
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