Digital & Technology Team (D&T) is an integral division of HEINEKEN Global Shared Services Center. We are committed to making Heineken the most connected brewery. That includes digitalizing and integrating our processes, ensuring best-in-class technology, and embedding a data-driven culture. By joining us you will work in one of the most dynamic and innovative teams and have a direct impact on building the future of Heineken!

Would you like to meet the Team, see our office and much more? Visit our website: Heineken (heineken-dt.pl)

Your responsibilities would include:

 

building and evolving the MLOps framework for running, monitoring, and deploying ML pipelines

designing and maintaining platform components to automate and simplify ML workflows

developing production-grade ML libraries, algorithms, and CLI tooling

building and maintaining a FastAPI backend to expose results and trigger simulations/optimizations

automating workflows using Databricks Workflows and integrating with the Azure stack (Azure ML, ADF, Azure Functions, ADLS, Web Apps, Redis, etc.)

developing and enhancing end-to-end machine learning pipelines

optimizing data ingestion and feature engineering processes for large-scale applications

contributing to CI/CD processes with Azure DevOps

collaborating closely with Data Scientists and Engineers to improve the developer experience

conducting code reviews and ensuring best engineering practices (testing, standards, modularity).

 

You are a good candidate if you have:

 

at least 3 years of experience as an MLOps or ML Engineer in production environments, combined with software engineering experience strong Python programming skills experience related to using ML infrastructure at scale experience in writing production code for machine learning models solid coding skills and software development experience experience with Azure DevOps and CI/CD pipelines working knowledge of Databricks and PySpark ability to design clean, modular APIs and internal tools fluency in extracting information from databases and good SQL skills understanding of fundamental data science concepts and experience with common tooling and packages used for machine learning.

 

Nice-to-have:

 

experience with FastAPI or similar frameworks familiarity with MLflow, or Azure ML pipelines experience building internal platforms or tooling for ML/DS teams understanding of orchestration patterns and scalable ML infrastructure.

 

At HEINEKEN Kraków, we take integrity and ethical conduct seriously. If someone has concerns about a possible violation of legal regulations indicated in Polish Whistleblowing Act or our Code of Business Conduct, we encourage them to speak up. Cases can be reported to global team or locally (in line with the local HGSS Whistleblowing procedure) by selecting proper option in this tool or by communicating it on hotline.

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