Head of ML & MLOps Engineering - Fintech Engineering

InPost is building a scale-up with AI deeply integrated, backed by the executive team. The role is part of the core Data & AI leadership to build the ML and MLOps function from zero with extreme ownership from model idea to its profit and loss impact.

• Leadership experience building and managing a team from zero.
• Hands-on expertise with AI, understanding models, pipelines, and serving layers.
• Experience across full ML lifecycle: development, validation, deployment, monitoring, retraining.
• Experience in credit-scoring, underwriting modelling, or comparable high-stakes ML.
• Skilled in model-risk management and responsible AI governance.
• Fluent English (B2+).

Bonus:

• Familiarity with CCD2, consumer-credit regulation, DORA/ICT risk, IFRS 9 model output implications.
• Experience with fraud-detection ML.
• Experience with Databricks/Spark platform.

• Build a production ML platform with serving, monitoring, reproducibility, and retraining engineered from the start.
• Develop credit and decisioning models with rigorous validation, champion/challenger testing, and explainability.
• Implement responsible AI practices, including model risk, bias checks, and independent sign-off gates before production.
• Develop agent-first systems with orchestration, guardrails, evaluations, and observability.
• Manage models built on a point-in-time-correct feature store.
• Run the ML business function managing compute budget, headcount, and return on investment.
• Own the ML & MLOps team development and hiring.
• Define model-development standards and validation methodology suitable for regulatory scrutiny.
• Coordinate clear ownership between feature production and model consumption with Data Engineering leadership.