Head of ML & MLOps Engineering - Fintech Engineering

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Description

Build ML that makes money and stands up to a regulator.We are building a scale-up inside InPost, and AI will flow through it. You would join the core Data & AI leadership team and build the ML and MLOps function from zero, with the InPost executive team backing it. Our word is extreme ownership: you own a model from first idea to its profit and loss impact. The mission Build a state-of-the-art ML platform and the discipline around it.Models with a price tag. Every model has a business case and a measurable monetary outcome.Credit and decisioning models built with rigorous validation, champion/challenger testing and explainability.A production ML platform. Serving, monitoring, reproducibility and retraining are engineered, not improvised.Responsible AI, built in. Model risk, bias and explainability checks, with an independent sign-off gate before anything reaches production.Agent-first systems. Agents are production components with orchestration, guardrails, evals and observability.◆ Models on governed data. You build on a point-in-time-correct feature store, not around it.This is a business function. Every model carries monetary value, and you will run the function that way: compute budget, headcount and return on investment. What you'll ownThe agentic standard for ML. You run agentic model iteration and agentic model monitoring and observability, bound to the feature store. You own the reliability, cost and latency of agent loops and graphs in production, and you hire agains

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