DeepSim is building a new type of physics simulator that radically scales and accelerates simulations for engineering teams. By combining breakthrough AI approaches with traditional numerical methods, we deliver simulation capabilities that were previously too slow or computationally costly. We are currently partnering with leading semiconductor companies to solve critical challenges in next-generation chip design, thermal management, and system architecture. Join us if you’re excited to reinvent how physics simulations are built, applied, and scaled.

We are looking for a Fluid Simulation Engineer with deep expertise in numerical simulation of fluid flow. You’ll play a key role in advancing DeepSim’s core simulation engine by designing solvers, modeling complex flow regimes, and enabling high-performance inference for large-scale engineering use cases.

Responsibilities

• Develop, implement, and optimize CFD/FEM-based fluid solvers for convection and heat transfer PDEs with multiphysics interactions.
• Investigate and enhance solver stability, accuracy, and performance across a variety of regimes and geometries.
• Build core simulation components and modeling pipelines that support AI-driven simulation frameworks.
• Collaborate with AI and systems engineers to create hybrid numerical/ML simulation architectures.
• Evaluate new numerical techniques, discretization strategies, and high-performance computing optimizations.

Qualifications

• Strong background in fluid simulations using CFD or FEM methods.
• Deep understanding of numerical solver mechanics and experience building CFD/FEM tools from scratch or modifying existing open-source frameworks.
• Proficiency in Python and C/C++, with experience writing high-performance and maintainable scientific code.
• Familiarity with HPC environments, GPU acceleration, or distributed computing is a plus.
• Master’s or PhD in engineering, applied physics, or a related discipline.