Computational Fluid Dynamics Engineer

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UniversalAGI
San Francisco, CALIFORNIA, United States
  • Finance
  • FullTime
  • Applications have closed

📍On-site | Full Time | Competitive Compensation | 🚀 Stealth AI Startup | Looking for Full Time Computational Fluid Dynamics Expert

Senior CFD Expert

Location: On-site, San Francisco

Commitment: Full Time Employment

Who We Are

UniversalAGI is a San Francisco-based startup backed and advised by Elad Gil (#1 Solo VC), Eric Schmidt (former Google CEO), Prith Banerjee (ANSYS CTO), Ion Stoica (Databricks Founder), Sebastian Thrun (Waymo Founder), Prof. Steven Brunton (AI for Physics Pioneer), Jared Kushner (former Senior Advisor to the President), David Patterson (Turing Award Winner), and Luis Videgaray (former Foreign and Finance Minister of Mexico). We’re building foundation AI models for physics that enable end-to-end automation from initial design through optimization, validation, and production.

We’re building a high-velocity team of relentless researchers and engineers that will define the next generation of engineering tools. If you’re passionate about AI, physics, or the future of industrial innovation, we want to hear from you.

Key Responsibilities

  • Guide the development of revolutionary new foundation AI models for physics.

  • Provide deep industry expertise in Computational Fluid Dynamics to inform AI-driven simulation models.

  • Interface with clients to define benchmark datasets, workflows, and validation criteria.

  • Advise AI research team on model fidelity, thermodynamics, aerodynamics, turbulence modeling, defeaturing, and mesh design.

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

Basic Qualifications

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

  • 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.

Preferred Qualifications

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