Databricks (Workflows, Unity Catalog, Lakehouse Monitoring) At Grape Up, we transform businesses by unlocking the potential of AI and data through innovative software solutions. We partner with a leading European airline to bring its machine learning models into reliable, production-grade operation. You will join a central MLOps capability that is deployed into product teams across the commercial, revenue management and operations domains – helping data scientists take forecasting, pricing and optimization models from notebooks to monitored, cost-efficient production workloads on Databricks. Responsibilities
Partner with data scientists across commercial, revenue management and operations teams to take their models and algorithms from experiments and notebooks into reliable production workloads Read, review and refactor existing data science code in Python – adding tests, improving structure and migrating notebooks into a standardized, production-ready project template Build and maintain CI/CD pipelines and Databricks Workflows for batch training and inference, with results written back to Lakehouse tables Apply MLOps best practices consistently across projects: experiment tracking, model versioning and registry (MLflow, Unity Catalog), reproducibility and safe rollback Design model-specific monitoring strategies together with data scientists – going beyond generic metrics to track the parameters, coefficients and data signals that matter for each model (incl. Databricks Lakehouse Monitoring) Optimize batch inference pipelines for performance and cloud cost Contribute to shared templates, standards and ways of working of a growing central MLOps capability Requirements
Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Engineering or a related field 4+ years of professional experience in MLOps, ML Engineering or software engineering with a strong focus on production ML systems Strong Python skills and solid software engineering practices – clean code, unit and integration testing (e.g., pytest), refactoring of existing codebases Strong hands-on experience with the ML lifecycle (experiment tracking, model registry, versioning, deployment), ideally with MLflow on Databricks. Solid understanding of machine learning fundamentals – able to discuss model behaviour, features and statistical properties with data scientists, not only the code Hands-on experience with Databricks (Workflows, notebooks, Unity Catalog) and MLflow (experiment tracking, model registry) Experience building CI/CD pipelines for ML projects (e.g., GitHub Actions, Azure DevOps, GitLab CI) Experience implementing model monitoring and observability for ML systems in production Experience with at least one cloud platform (AWS or Azure) Strong communication skills – comfortable working directly with data scientists and business stakeholders in an international environment Fluency in English, both written and spoken Nice to have
Databricks Certification Experience with Databricks Asset Bundles and infrastructure-as-code (e.g., Terraform) Experience optimizing Databricks batch workloads for performance and cost (e.g., PySpark, cluster configuration) Background in forecasting, pricing or optimization models (e.g., revenue management) Experience in the aviation, travel or e-commerce domain Recruitment owner Employee referral Knowledge platforms Equipment Integration activities Employee referral Knowledge platforms Equipment Integration activities Employee referral Knowledge platforms Equipment Integration activities Employee referral Knowledge platforms Equipment Integration activities Employee referral Knowledge platforms Equipment Integration activities Employee referral Knowledge platforms Equipment Integration activities Lunch & Learn In-house Tech Up Lunch & Learn In-house Tech Up Lunch & Learn In-house Tech Up Lunch & Learn In-house Tech Up Conferences & training Feedback sessions Business travel opportunities Conferences & training Feedback sessions Business travel opportunities Conferences & training Feedback sessions Business travel opportunities Conferences & training Feedback sessions Business travel opportunities
#J-18808-Ljbffr
Senior MLOps Engineer (Databricks) in Białystok – pracodawca: Grape Up
Aiboostr to doskonały pracodawca, który oferuje wyjątkowe możliwości rozwoju kariery w dynamicznie rozwijającym się obszarze sztucznej inteligencji. Pracując w zespole pełnym pasjonatów, będziesz miał szansę na samodzielne kształtowanie strategii sprzedaży oraz bezpośrednią współpracę z liderami branży, co sprzyja nie tylko osobistemu rozwojowi, ale także budowaniu wartościowych relacji zawodowych. Dodatkowo, elastyczne warunki pracy oraz transparentny system wynagrodzeń sprawiają, że Aiboostr jest miejscem, gdzie Twoje osiągnięcia są doceniane i nagradzane.
