Senior Machine Learning Research Engineer / Applied Scientist (H/F)
Core
Design experimental protocols to evaluate Machine Learning approaches for time series forecasting and IoT data, focusing on predictive maintenance and anomaly detection.
Role type
Senior Machine Learning Research Engineer (Applied Scientist)
Builds
Production-ready ML components for forecasting and anomaly detection within an agentic framework
Domain
Industrial IoT, Predictive Maintenance, Time Series Analysis
Deliverable
production ML models
Required skills
Python, Machine Learning, Deep Learning, Time Series Modeling, Anomaly Detection, Survival Analysis, Experimental Design, Robust Software Development, Temporal Validation, Reproducibility
Preferred skills
Multi-Agent Systems, Dataiku, MLOps, Cloud, Scientific Publishing
Technologies
Python, Dataiku, MLOps, Cloud
Responsibilities
Design and execute rigorous experimental protocols for ML approaches; Develop and evolve components for forecasting and IoT data; Model the influence of external events on time series; Build and compare forecasting scenarios; Develop anomaly detection and failure precursor signal approaches; Ensure absence of temporal leakage in experiments; Construct baselines and perform retrospective evaluations; Measure model robustness and generalization; Develop robust, tested, and documented Python code; Ensure reproducibility and traceability of experiments; Present results and recommendations to technical and business teams; Facilitate knowledge transfer to internal teams.
Seniority
Senior, hands-on IC with research focus