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This is a rare opportunity to blend ML, AI, and real business impact. You’ll be joining a high growth, cloud-native technology company that has recently completed a major late stage funding round and on their way to an IPO in the near future! This role offers the best of both worlds: the scale, profitability, and market presence of an established leader, combined with the autonomy, ownership, and speed typically found in a startup environment. As the first hire in a newly formed AI/ML team in London, you’ll play a foundational role in setting technical direction, defining best practices, and embedding AI across the organisation in a way that delivers measurable business impact. In this role, you’ll sit at the intersection of AI, data, and business operations. Your work will be visible, practical, and used. You’ll partner closely with multiple other global teams to understand where friction exists today and how AI can meaningfully improve outcomes. A significant part of your work will involve exploring organisational data, understanding its structure, quality, and limitations and turning that insight into robust AI driven systems. You’ll design and deliver end-to-end ML solutions, from research and prototyping through to production ready pipelines, workflows and agents that are scalable and reliable.
Job Responsibility:
Play a foundational role in setting technical direction, defining best practices, and embedding AI across the organisation
Sit at the intersection of AI, data, and business operations
Partner closely with multiple other global teams to understand where friction exists today and how AI can meaningfully improve outcomes
Explore organisational data, understanding its structure, quality, and limitations
Turn insight into robust AI driven systems
Design and deliver end-to-end ML solutions, from research and prototyping through to production ready pipelines, workflows and agents that are scalable and reliable
Requirements:
Strong hands on experience in AI/ML development
Several years’ experience building AI-driven systems in Python
Exposure to MLOps or workflow orchestration
Solid understanding of how data flows through real organisations
Background in Data Science or Machine Learning evolving into modern ML engineering