Machine Learning Engineer – MLOps, Software Engineering

Jobtailor; Deutschland; Vor Ort; EUR 70.000 - 110.000; Vollzeit

Zusammenfassung

Jobtailor sucht einen Backend-Softwareingenieur mit starker Python-Expertise zur Weiterentwicklung unserer Services im Bereich Routenplanung und operativer Estimatoren. Sie arbeiten eng mit Data Scientists zusammen und bringen Modelle zuverlässig in die Produktion.

Zu Ihren Aufgaben gehören der Aufbau/Unterhalt von Daten- und Training-Pipelines in Databricks sowie die Implementierung robuster CI/CD-Pipelines in Azure DevOps. Deutschsprachiges Umfeld, englische Fachkommunikation.

Qualifikationen

• Proficient in Python for backend services in production.
• Experience with automated testing (pytest) and well-structured tests.
• Experience with cloud environments and CI/CD pipelines.
• Understanding of ML training/inference paths and feature pipelines.

Aufgaben

• Work on backend services for route-planning estimator and other estimators.
• Ensure code quality and architectures in ML repositories.
• Collaborate with Data Scientists to productionize models and pipelines.
• Develop and operate data/training pipelines in Databricks.
• Build and maintain CI/CD pipelines in Azure DevOps with tests and deployments.
• Analyze production incidents and derive sustainable improvements in code and processes.

Kenntnisse

Python (backend)

Automated testing

Cloud environments

CI/CD

ML concepts familiarity

German language communication

Tools

Databricks

Azure DevOps

pytest

Jobbeschreibung

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.
• Take responsibility for code quality and structure in our ML repositories (reviews, refactorings, architecture).
• 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.