About Navier AI
Navier AI is a venture-backed startup building 1000x faster Computational Fluid Dynamics simulations using ML.
Why
Engineers today use simulation tools that are slow, expensive, and overly complex. At many companies, the small analysis teams are usually PhDs with years of experience in using these esoteric products. This results in slow design iterations and performance left on the table.
Despite these performance and usability issues, simulations are crucial in modern engineering for everything from the design of hair dryers to rockets to F1 Cars.
How
At Navier AI, we believe the future of engineering is digital, in which fast, high-quality simulations drive the design of everything from aircraft to heatsinks. We are building advanced physics-ML models to enable fast physics simulators for simulation-driven design.
Our first product is a web app for fluid dynamics simulations and design optimization.
About This Role
Navier AI is hiring a Full Stack Engineer to help build the next generation of engineering software. As a Full Stack Engineer, you’ll work with the Founders on developing web apps for complex engineering tasks such as fluid simulations and structural analysis. We are commercializing physics-ML for engineering design and optimization. You’ll be individually contributing across the tech stack - some days you’ll work on new web app features and others you’ll optimize server-side rendering.
Qualifications
- Passion to build the future of engineering software, curious to learn new skills, and willing to wear multiple hats
- Comfortable building end-to-end web applications
- Strong background in full-stack web development
- Experience with cloud providers such as AWS, Azure, and GCP
- Experience with data security
- Proficiency with modern web frameworks (E.g. React, Vue, Nuxt)
- Bachelor’s degree or higher in Computer Science or Software Engineering
Bonus Points if you have
- Understanding or experience building web applications for scientific machine learning or scientific visualization
- Understanding of numerical methods for Computational Fluid Dynamics
- Experience with scientific visualization frameworks such as Paraview, VTK, or Trame