Head of ML & MLOps Engineering – Fintech

• Build the ML and MLOps function from zero
• Build a state-of-the-art ML platform and the discipline around it
• Develop credit and decisioning models with rigorous validation, champion/challenger testing and explainability
• Engineer production ML serving, monitoring, reproducibility and retraining
• Implement responsible AI, including model-risk, bias and explainability checks with an independent sign-off gate before production
• Build agent-first production systems with orchestration, guardrails, evaluations and observability
• Use a point-in-time-correct feature store and governed data
• Own the ML & MLOps team from the first hire onward
• Establish model-development standards and validation methodology for model-risk and regulatory scrutiny
• Own the ML platform behind decisioning services
• Define ownership between feature production and model consumption with Data Engineering leadership
• Manage compute budget, headcount and return on investment

• Experienced across the full ML lifecycle: development, validation, deployment, monitoring and retraining
• Experienced in credit-scoring or underwriting modelling, or comparable high-stakes ML
• Skilled in model-risk management and responsible-AI governance
• Experienced in building and leading a team from zero
• Fluent in English (B2+)
• Suggested 7+ years in ML and 3+ years leading
• Bonus: CCD2 and consumer-credit regulation
• Bonus: DORA/ICT risk
• Bonus: IFRS 9 implications for model outputs
• Bonus: fraud-detection ML
• Bonus: Databricks/Spark

• Seat at the table on a core leadership team
• Build it right the first time with no legacy ML estate
• Real pace in a lean, AI-native organisation
• Employees can work remotely