6 days ago
Warsaw, Poland or Kraków, PolandStaff+
Responsibilities
- Set ML architecture and modelling standards for credit-scoring and merchant-underwriting models.
- Own the end-to-end model lifecycle from feature selection and training methodology through validation, deployment, and post-production monitoring.
- Partner with Data Engineering on point-in-time-correct production features and shape the feature-store roadmap.
- Establish model documentation, model cards, adverse-action reasoning, and regulatory model-risk practices.
- Design and codify agentic harnesses and loop/graph workflows for model iteration, evaluation, retraining, promotion, monitoring, and observability.
- Set technical direction, review designs and code, and mentor Senior and Mid ML Engineers.
- Collaborate with Credit Risk and engineering teams integrating models into decisioning services.
Requirements
- 7+ years of experience in production machine learning engineering.
- 3+ years of experience in credit-scoring, risk modelling, or decisioning ML using Spark/Databricks or an equivalent lakehouse.
- 7+ years of expert Python and ML-framework experience with scikit-learn, XGBoost, and PyTorch.
- Strong experience designing credit-risk and underwriting models, including scorecards, gradient boosting, and survival or behavioural models.
- Experience with model validation methodologies including back-testing, champion/challenger testing, population stability, and calibration.
- Experience with point-in-time-correct feature engineering, feature-store consumption, and MLOps tooling including MLflow.
- Fluency in explainability and responsible-AI techniques including SHAP, model cards, and adverse-action reasoning.
- Working knowledge of regulatory model-risk frameworks and deep knowledge of LLM behaviour and trade-offs.
- 3+ years of experience with agentic coding tools, harnesses, context and tool design, evaluations, guardrails, and loop or graph engineering.
- Staff-level technical leadership through influence, mentoring, and design and code review.
- Fluent English at B2+ level.
- Preferred experience includes FinTech, lending or payments ML, model-risk management, regulatory validation, MLOps or feature-store ownership, fraud modelling, low-latency serving, regulator-facing documentation, and causal inference or uplift modelling.
Benefits
- Architectural authority from day one on a greenfield, high-stakes fintech platform.
- Modern stack, lean AI-native team, autonomy, and room to experiment with new technologies.
- Hybrid work, ideally one day per week in the Warsaw or Kraków office.
- B2B contract.
Tech Stack
Categories
About InPost
InPost is a public logistics company listed on Euronext Amsterdam that builds and operates an out-of-home parcel delivery network for e-commerce. Its network includes more than 50,000 out-of-home pick-up points, including over 27,000 parcel lockers, plus to-door courier and fulfillment services for online merchants across Poland, the UK, Italy, Iberia, France and Benelux. Headquartered in Luxembourg, it acquired French operator Mondial Relay in 2021.