Senior Machine Learning Engineer (FinTech / MLOps / Agentic AI)

120 - 170 PLN/ godz./ godz.B2BB2B (netto)

SeniorHybryda·KrakówFull-time·B2B

#476450·Dodano 2 dni temu·0

Źródło: People More

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Tech Stack / Keywords

Python SQL Spark DatabricksMLOpsSHAPLIMELLMs CI/CDfeature store

Podsumowanie oferty

Design and operate machine learning models for credit scoring and merchant underwriting in a FinTech project. The role covers the ML lifecycle, MLOps, and agentic AI workflows supporting BNPL and MCA decisioning.

Wymagania

Strong commercial experience in Machine Learning Engineering, including building and operating ML solutions in production environments.
Hands-on experience across the full ML lifecycle: feature engineering, model training, validation, deployment, and monitoring.
Very good knowledge of Python and SQL.
Practical experience with Spark and/or Databricks in large-scale machine learning environments.
Strong understanding of model validation techniques, including backtesting, Population Stability Index (PSI), Gini/KS metrics, and model calibration.
Experience with MLOps, including model registries, versioning, CI/CD pipelines, model monitoring, drift detection, and automated alerting.
Knowledge of champion/challenger testing and shadow deployment strategies.
Practical experience with feature stores and point-in-time-correct feature engineering.
Familiarity with model explainability methods such as SHAP and LIME, and preparing technical and validation documentation.
Experience developing advanced agentic AI workflows, including agent orchestration, loop and graph design, context management, tool integration, guardrails, and evaluation frameworks.
Good understanding of Large Language Models (LLMs) and their practical application in engineering workflows.
Ability to design and deliver reliable, observable, and cost-efficient ML systems.
Strong analytical skills, independence, and a hands-on approach to problem-solving.
Ability to collaborate effectively with engineering, data, and business teams.
Very good English and Polish.

Obowiązki

Design, develop, and deploy machine learning models for credit scoring and merchant underwriting across the full ML lifecycle.
Build point-in-time-correct features using a shared feature store to support BNPL (Buy Now, Pay Later) and MCA (Merchant Cash Advance) decisioning.
Cooperate with Data Engineering teams to establish data source contracts, quality requirements, and data freshness SLAs.
Design and maintain agentic workflows, including agent loops, orchestration graphs, context management, tool integrations, evaluation mechanisms, and guardrails.
Implement MLOps processes, including model versioning, automated CI/CD pipelines, and champion/challenger or shadow deployment strategies.
Monitor production models for data drift, population stability, and performance degradation; implement retraining, recalibration, or rollback mechanisms.
Ensure model explainability and regulatory compliance through documentation, validation evidence, and explainability techniques.
Support regulatory and audit requirements, including CCD2 creditworthiness assessment.
Develop automated validation and backtesting frameworks integrated with the MLOps pipeline.
Build and maintain automated experimentation, evaluation, retraining, and model promotion workflows.
Optimize the reliability, observability, and operational costs of ML and agentic AI systems.

Benefity

Private medical care.
Sports card.
Training courses.
Opportunity to attend conferences, including as a speaker.
Support with publishing in recognized magazines and online.

Opieka zdrowotna

Karta sportowa

Inne informacje

The recruitment process includes a remote initial interview, a remote technical talk, and a decision to work together.

People More

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