Scientific ML Engineer

Overview

On Site
Hybrid
Depends on Experience
Contract - Independent
Contract - W2
Contract - 12 Month(s)

Skills

CAD
GPU

Job Details

Requirements
Core Deep Learning Experience (3+ years)
Hands-on deep learning training with scientific datasets: CAD geometries, CFD
simulations, or similar physical data
End-to-end model development: data preparation, training, hyperparameter tuning
Multi-GPU training and GPU memory optimization
PyTorch and PyTorch Lightning proficiency
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.

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