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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
About Us RACEON ARE YOUR TRACKSIDE SPECIALISTS ensuring peak performance is delivered where it counts the most - on race day. Our engineers are highly specialised and motivated by success. They are coming from various fields of motorsport and are all high level candidates that can make the difference. We are available as talented individuals or as a consolidated group who are able to deliver at peak performance due to our understanding of each individual team members strengths.
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Sprachkenntnisse
- English
Hinweis für Nutzer
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