📍 San Francisco | 🏢 5 Days Onsite

Location: Onsite in San Francisco

Compensation: Competitive Salary + Equity

Who We Are

Engineering simulation is one of the last major categories of software that AI hasn't rebuilt. The tools used to design aircraft, ships, reservoirs, and medical devices still run on numerical methods that are decades old, and an engineer can wait a full day for a single answer. UniversalAGI is building foundation models that learn physics directly from data, and they are already running in early deployments on real computational fluid dynamics and reservoir engineering problems for some of the largest industrial and defense organizations in the world.

We are a team of 25 researchers and engineers in San Francisco backed by Elad Gil (#1 Solo VC), Eric Schmidt (former Google CEO), Ion Stoica (Databricks Founder), Jared Kushner (former Senior Advisor to the President), David Patterson (Turing Award Winner), and Luis Videgaray (former Foreign and Finance Minister of Mexico).

About the Role

As a founding Aerospace Simulation Engineer, you'll be in the arena from day one, building the future of AI for physics simulation with your own hands. This is your chance to take everything you've learned across the full spectrum of the aerospace flow regime – from subsonic to hypersonic – and use it to build foundation AI models that will transform how the entire industry works.

You'll work directly with the CEO and founding team to shape our product around the real pain points you've faced in your career: the tedious preprocessing, the manual mesh iterations, the endless parameter sweeps.

What You'll Do

Design, preprocess, mesh, simulate, and post-process aerodynamics and thermal simulations for aerospace configurations at unprecedented scale and speed

Come up with creative ways to design, mesh, and simulate hundreds or thousands of configurations systematically across flow regimes (subsonic, transonic, supersonic, hypersonic), building the data pipelines that will train our foundation models

Guide the development of our product and our revolutionary new AI models for physics by working directly on research problems with our AI team, bridging the gap between traditional CFD and cutting-edge ML

Work directly with clients to solve their problems and define benchmark datasets, validation criteria, and workflows that prove our models can match or exceed traditional simulation accuracy

Generate high-quality simulation data at scale, every simulation you run directly improves our foundation models

Advise the AI research team on the nuances that matter: compressible vs. incompressible flow, turbulence modeling across flow regimes, conjugate heat transfer, thermal analysis, shock interactions, and mesh design tradeoffs

Lead technical customer conversations with customers and internal teams, translating between the world of aerospace CFD and the world of AI

This is a role for someone who's ready to solve some of humanity's hardest problems, push past the limitations of traditional CFD, and build something that will define the next generation of industrial engineering.

Qualifications

3-5+ years of industry hands-on experience running aerospace CFD simulations, including preprocessing, simulation, post processing, and design iteration.

Strong experience with Star-CCM+ and OpenFoam as a primary solver

Experience across the flow regime spectrum: subsonic, transonic, supersonic, and hypersonic flows.

Solid background in heat transfer, thermal analysis/modeling, and conjugate heat transfer (CHT)

Deep understanding of fluid mechanics, compressible and incompressible flow, meshing, boundary conditions, and numerical methods

Strong communicator capable of bridging customers, engineering and research teams.

Outstanding execution velocity and delivery

Exceptional creativity, problem-solving ability, ambition, and attention to detail.

Comfortable working in high-intensity, fast-paced startup environments with evolving priorities and tight deadlines.

Bonus Qualifications

Master’s degree (or higher) in Aerospace Engineering, Mechanical Engineering, or a closely related field.