Public Sector | 30-10-2024
D&A Machine Learning Ops Engineer
Location: Hybrid Working (2 days in London)
Key Knowledge / Skills:
- Ability to balance competing tasks and demands effectively, such as ensuring that all assigned development tasks are prioritised and interdependences are worked through with the rest of the development team.
- Effective communication with non-technical stakeholders about complex technical concepts to effectively define and prioritise the features, refine the scope.
- Capable at actively listening to, negotiating with and managing conflicts, in order to determine scope and prioritisation for yourself and the team, and to effectively collaborate with stakeholders and other technical roles to identify problems, determine solutions, and effectively manage delivery of an integrated product across multiple development teams and technologies.
- Capable at continually assessing and improving product processes within their teams, product areas, and on the wider programme to enhance the efficiency and quality of product development, agile practise and product strategy.
- Solid understanding of machine learning concepts, techniques and frameworks to enable frameworks to be developed.
- Ability to ensure that data scientists can use ML models without having to worry about how they're built or maintained.
Experience:
- ML Ops Engineer experience of at least 3 years - ideally on large/national projects.
- Technical experience as an ML Ops Engineer:
- Experience of implementing ML models using the Azure stack.
- Experience in Python and Scala in relation to ML models