SciML Engineer

Applied SciML Engineer

We're looking for an engineer with deep expertise in scientific machine learning and

computational geometry to build production ML systems for physical simulation data.

Requirements

Core Deep Learning Experience (3+ years)

• Hands-on deep learning training with scientific datasets : CAD geometries, CFD

simulations, or similar physical data

Multi-GPU training and GPU memory optimisation

Technical Depth Demonstrated experience (via publications in top venues OR 3+ years

industry experience) in one or both areas :

Computational Geometry : PointNet, DGCNN, TripNet, MeshGPT, or similar geometric

deep learning architectures

Scientific ML : PINNs, DeepONet, FNO, Transformers for physics, SCoT, Poseidon, or

related physics-informed models

Evidence of Impact Publications in leading ML / computational science conferences / journals OR

proven track record building SciML systems in industry.