About the role
DeepSim is seeking an AI Physics Engineer to help build the next generation of fast, scalable physics simulation technology. This role is ideal for someone who has expertise at the intersection of modern AI models and physics-based modeling and who is excited to transform how engineers simulate complex physical systems.
Responsibilities
- Design and implement AI-accelerated physics models with a focus on thermal, mechanical, or fluid domains.
- Train, evaluate, and refine machine learning models to improve simulation speed, accuracy, stability, and generalization.
- Develop high-quality synthetic dataset generation pipelines.
- Contribute to research directions by identifying opportunities for new modeling approaches, data strategies, and performance improvements.
- Collaborate closely with physics, AI, and platform engineers to integrate models into production-grade simulation tools.
Qualifications
- Strong background in building and training AI or ML models, including dataset creation and preprocessing for scientific/engineering applications.
- Experience in physics simulations, ideally for thermal, solid mechanics, or fluid flow problems. Background in numerical methods and experience developing numerical analysis tools (especially for physics PDEs) are a big plus.
- Solid foundation in linear algebra.
- Proficiency with scientific computing tools (e.g., NumPy, PyTorch, JAX, or similar).
- Master’s or PhD in engineering, computer science, physics, applied math, or a related field.
- Comfort working in fast-paced research and production environments.
