Das ist der Job
Take responsibility for code quality and structure in our ML repositories (reviews, refactorings, architecture).
Darum lohnt es sich
Responsibilities Work on the backend services behind our route-planning estimator and other operational estimators (e.g., process durations, driver availability) and ensure their stability and maintainability. Work closely with our Data Scientists and reliably bring models and feature pipelines into production.
Develop and operate the associated data and training pipelines in Databricks. Build and maintain CI/CD pipelines in Azure DevOps – including automated tests and deployments. Ensure that our systems run reliably in the cloud environment, analyze production incidents and derive sustainable improvements for code and processes.
Requirements You have experience in professional software engineering and have independently contributed to production services or components: from implementation through reviews and tests to stable operation. You are highly proficient in Python in a production context and write structured, maintainable, and testable code.
You have experience with automated testing (e.g., pytest) and ensure well-designed unit and integration tests for your services. You have experience with cloud environments and CI/CD.
You understand fundamental ML concepts (training/inference paths, features, retraining, evaluation) well enough to understand our Data Scientists' models and pipelines and make them production-ready.
You can explain technical topics appropriately for the audience and are comfortable working in a German-speaking environment; you use English confidently in technical contexts. Core Competencies Proficient in Python for backend services, with a strong focus on code quality, maintainability, and automated testing.
Experienced in developing and operating data pipelines in cloud environments, particularly using Databricks and Azure DevOps. #J-18808-Ljbffr
