Short FactsLocation: Munich, GermanyEmployment Type: Full-Time, indefinite termSalary Range: € 95,000 – 115,000 per year gross, depending on seniority levelOffice First work setupLanguage Requirement: C1 Level EnglishYour ResponsibilitiesAct as the technical bridge between data science and software engineering, helping research models become reliable, maintainable production systems, and helping engineering understand what ML workloads actually needDesign and build the data and feature pipelines that support Flexa's forecasting and trading models at scale across hundreds of thousands of distributed systemsLeverage Flexa’s deployment, orchestration, and serving platform to bring models into production, for both batch and real-time workloadsEstablish monitoring and observability for models in production, like drift, data quality, latency, and failure modes Partner closely with data scientists on model design and validation, bringing an engineering perspective on scalability, maintainability, and production risk from early onChampion engineering rigor and ML best practices to foster an open, data-driven engineering culture.
Contribute to the technical roadmap, anticipating scaling needs as data volume and model complexity growOpportunity to guide and develop more junior colleagues through design review, code review, and structured feedbackBe part of a cross-functional team of data scientists, software engineers, and other teams across Flexa's partner ecosystem Your ProfileMandatory RequirementsUniversity degree in an engineering or analytical field (Computer Science, Mathematics, Physics, Statistics, Engineering or a related discipline)5+ years of engineering experience, with significant time spent supporting or building ML systems in productionProficiency in Python and software engineering best practices: testing, code quality, code review, CI/CD, monitoring, and modular code design Solid working knowledge of MLOps practices: pipeline setup, deployment, monitor.