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.

• 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)

• 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