General Information
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
