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Physics-Informed Machine Learning Engineer
Svitla
remote
Remote (Europe)
About this role
Role overview Svitla Systems Inc. is looking for a Physics-Informed Machine Learning Engineer for a full-time position (40 hours per week) in Europe. Our client is a technology startup.
Requirements
- Experience in building and training physics-informed models — a physics-based term in the loss function of a real project (PINN, physics-regularized NN, or equivalent).
- Strong understanding of time-series/sequence modeling (LSTM, temporal CNN, transformers, or state-space models) on sensor or telemetry data.
- Understanding of parameter calibration / inverse problem: fitting mechanistic model parameters to noisy observational data (Bayesian calibration, MLE, or optimization-based).
- Expert knowledge of Python scientific stack (Pandas, NumPy, scikit-learn, PyTorch, or JAX) and be comfortable owning a data pipeline end to end, including data-quality investigation.
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