Über
RaceOn is seeking a Senior Machine Learning Engineer as well as a Junior Machine Learning Engineer to architect and build production ML systems that create a competitive advantage on race day. The tasks are slightly different but candidates will be managed via the same application and more details will be available in the interview. A generalization of tasks is listed below as well as profile requirements. Any applications not matching minimum profile requirements will be ignored. Your Mission
Develop, validate, and deploy ML models for performance and operational use cases (e.g., predictive analytics, decision support, performance measurement) Build data pipelines and analysis workflows for structured and time-series data Implement monitoring and iteration practices for deployed models (MLOps basics) Collaborate with engineering and performance stakeholders to translate requirements into deliverables Contribute to ML infrastructure and codebase quality (reviews, documentation, reusable components) Travel occasionally for live validation and stakeholder feedback (role dependent; approx. 5–6 race weekends/year for some assignments) Your Profile
2+ years building production ML systems MSc in Machine Learning, Data Science, Computer Science, or related field (or equivalent experience) Strong Python and experience with ML libraries (scikit-learn and/or PyTorch/TensorFlow) Experience with data handling and querying (SQL) Understanding of model evaluation, deployment concepts, and version control (Git) Ability to work in complex engineering environments and communicate with non-ML stakeholders Advantageous would be: time-series forecasting, optimization, real-time systems, dashboards, sports/motorsport analytics, AWS experience. Work Location USA | Remote possible (role-dependent) | Limited Travel required
Sprachkenntnisse
- English
Hinweis für Nutzer
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