ML Engineer

Hyperion Polymer Production Online Software (HYPPOS) is an industrial process intelligence platform deployed across polymer manufacturing plants in Europe and the Middle East. The platform integrates real-time batch tracking, on-line polymer analysis, and machine learning soft sensors to reduce off-spec output, grade-transition waste, and energy consumption at industrial scale.

• Architect and implement model pipelines for multi-quality-parameter prediction in continuous polymer processes;
• Design and own the online and incremental learning strategy to maintain model accuracy under process variability and distribution shift;
• Develop model logic for dynamic operating scenarios including steady-state production, grade transitions, and start-up and shutdown phases;
• Lead model validation, uncertainty quantification, and explainability reporting;
• Collaborate with the software engineering team to define ML service interfaces, data contracts, and deployment pipelines;
• Mentor the junior ML engineer and contribute to internal knowledge transfer and documentation;
• Participate in customer-facing technical reviews at deployed sites;
• Contribute to project reporting, milestone documentation, and technical deliverables.

• MSc or PhD in Machine Learning, Computer Science, Applied Mathematics, or a closely related field;
• 5+ Years of hands-on experience developing and deploying ML models in production environments;
• Strong grounding in time-series modelling, regression, and probabilistic methods;
• Proven experience with ensemble methods and advanced model architectures;
• Proficiency in Python and the standard ML stack: PyTorch or TensorFlow, scikit-learn, NumPy, Pandas;
• Experience with online, incremental, or adaptive learning approaches;
• Solid understanding of model explainability techniques (SHAP, LIME, or equivalent);
• Fluent in English;
• Nice to have: Background in industrial process modelling, chemometrics, or soft-sensor development, familiarity with polymer manufacturing or continuous chemical processes, experience with MLflow, DVC, or similar experiment tracking and model management tooling, prior work in R&D projects or an applied research environment, publications or conference contributions in applied ML or process intelligence.

• Competitive salary commensurate with experience;
• Technically ambitious project at the frontier of industrial AI;
• Collaborative team with deep domain expertise in polymer manufacturing.