Applied Scientist - All Levels
Core
Building physical foundation models and AI-driven simulation software for engineering and manufacturing in advanced industries.
Role type
Applied Scientist (Research)
Builds
AI-native engineering simulation stack and physical foundation models
Domain
Deep-tech, AI, Numerical Physics, Aerospace & Defense, Materials, Energy, Semiconductors, Automotive
Deliverable
production ML models
Required skills
Deep learning, probabilistic methods, operator learning (neural operators), geometric deep learning, generative models (VAEs, Diffusion Models), Python, PyTorch, JAX, high-dimensional data modeling, network architecture design, experimental pipeline design, technical writing
Preferred skills
Experience with PDEs, 3D computer vision, spatiotemporal data, publication record in top-tier venues (NeurIPS, ICML, etc.)
Technologies
Python, NumPy, SciPy, Pandas, PyTorch, JAX
Responsibilities
Translate physics/engineering challenges into mathematical formulations, build ML models for physical system prediction, iterate on model architectures and training strategies, own research work-streams, communicate results to colleagues and customers, publish research papers
Seniority
All Levels (Junior to Senior/Principal)