Responsibilities
- Design, build, and deploy machine learning models that solve real business problems.
- Focus on production-ready systems that directly influence product performance, user behavior, and revenue, not just offline experiments.
- Take ownership from experimentation to deployment and beyond.
- Validate models, ship them into production, monitor their performance, and continuously iterate to improve outcomes in dynamic environments.
- Work closely with Data Scientists and Analysts to translate insights, metrics, and hypotheses into scalable ML solutions.
- Partner with Data Engineers to ensure robust data pipelines, feature availability, and reliable model deployment.
- Help define how ML is done at exmox by establishing best practices, tooling, and architecture for model development, deployment, versioning, and monitoring.
- Build the foundation for future scale in ML infrastructure and practices.
- Take loosely defined problems and turn them into structured ML solutions.
- Make trade-offs, define approaches, and bring clarity where none exists yet.
Work Arrangement
Hybrid
Team
Structure: Cross-functional collaboration with Data Science, Data Engineering, and Product teams.
Additional Information
- This is not a remote-only position.
- Flexible hybrid work model in Hamburg, Germany.
- Work from home on Mondays & Fridays.
- Office attendance on Tuesdays, Wednesdays, and Thursdays.
