Senior MLOps Engineer (Databricks)

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

Benefits

• Non-corporate work environment among experienced engineers
• Individual growth & development plan supported by cyclical feedback sessions
• Access to knowledge platforms (e.g. Pluralsight)
• Equipment of your choice
• Financing of conferences, external trainings, and certifications
• Language lessons (English, German and Polish for foreigners)
• LuxMed private medical care
• Weekly Lunch & Learn where we meet up in the office, lunch together, and share our knowledge
• Employee referral program
• Rewards for the success of the month and year awarded by our employees
• Special rewards for your years with us (G-Man)
• Integration activities