Physics-Informed Machine Learning Engineer

Role overview

Svitla Systems Inc. is looking for a Physics-Informed Machine Learning Engineer for a full-time position (40 hours per week) in Ukraine. Our client is a technology startup.

The team is building a Physics-Informed Foundational Model to understand GPU and compute health. They derive physics-grounded stress signals: effective-stress proxies, semiconductor degradation estimates, and dynamical mathematical features, and use them to assess hardware health over time. The feature pipeline runs end-to-end. You'll build the model and the fusion layer on top of it. You will own the modeling: designing the fusion layer (how physics-based and dynamical features combine into a coherent health signal) and the temporal modeling layer (a physics-informed model, PINN-style, where empirical stress signals drive part of the loss and a physics-based degradation model informs another part).