Computational Fluid Dynamics Engineer

UniversalAGI — CFD Industry Expert

UniversalAGI
UniversalAGI is an AI for Physics company based in San Francisco, backed by world-class investors including Elad Gil, Eric Schmidt, Ion Stoica, and David Patterson. We’re building the foundational intelligence layer for physics — accelerating design, simulation, and experimentation across industries like aerospace, automotive, semiconductors, materials, and energy.

Our work integrates modern machine learning with computational physics, turning months-long engineering loops into real-time insight. We operate in person in San Francisco, with a small, high-velocity team of builders obsessed with customer outcomes, scientific depth, and shipping breakthroughs that matter.

If you thrive on technical intensity, learning from brilliant peers, and creating impact measured in equations solved and customers transformed — this is your place.

What You’ll Do

• • Bring deep expertise in Computational Fluid Dynamics to guide AI-driven simulation models.

• • Work with customers to define benchmark datasets, workflows, and validation criteria.

• • Advise researchers on model fidelity, thermodynamics, aerodynamics, turbulence modeling, defeaturing, and mesh design.

• • Lead technical conversations bridging traditional CFD and ML-based approaches.

Who You Are

• • 7+ years of experience in CFD, aerospace, or automotive simulation.

• • Expert in solver frameworks (OpenFOAM, Fluent, STAR-CCM+, or similar).

• • Deep understanding of fluid mechanics, boundary conditions, and numerical stability.

• • Strong communicator capable of bridging engineering and research teams.

Nice to Have

• • Prior experience integrating AI models or PINNs into simulation pipelines.

• • Industry exposure to automotive, aerospace, or energy applications.

All roles are full-time and based in person at our San Francisco office.

UniversalAGI — AI Research Leader

About UniversalAGI
UniversalAGI is an AI for Physics company based in San Francisco, backed by world-class investors including Elad Gil, Eric Schmidt, Ion Stoica, and David Patterson. We’re building the foundational intelligence layer for physics — accelerating design, simulation, and experimentation across industries like aerospace, automotive, semiconductors, materials, and energy.

Our work integrates modern machine learning with computational physics, turning months-long engineering loops into real-time insight. We operate in person in San Francisco, with a small, high-velocity team of builders obsessed with customer outcomes, scientific depth, and shipping breakthroughs that matter.

If you thrive on technical intensity, learning from brilliant peers, and creating impact measured in equations solved and customers transformed — this is your place.

What You’ll Do

• • Lead a small, world-class research group pushing the boundaries of AI for physics.

• • Develop new machine learning models for physics models, neural operators, PINNs, and multi-fidelity models.

• • Translate research outcomes into practical systems used by customers.

• • Build bridges between academia and product — moving research from paper to production.

Who You Are

• • PhD or equivalent experience in ML, Physics, or Applied Math.

• • Demonstrated research leadership (publications, patents, or deployed systems).

• • Deep understanding of modern AI (Transformers, Diffusion, GNNs, VAEs) and their physical applications.

• • Comfortable working with engineers to operationalize research outcomes.

Nice to Have

• • Background in CFD, FEM, or scientific computing.

• • Experience mentoring researchers in fast-moving environments.

All roles are full-time and based in person at our San Francisco office.