AI Physics Engine to replace simulations and prototypes. Backed by Y Combinator.
About the role
Our vision is to make the universe computable. Every pattern of nature, every equation, every experiment, instantly at your fingertips. We’re looking for a Founding SWE who thrives on building systems end-to-end: someone who can take cutting-edge ML models and turn them into production-ready applications, iterate quickly with users, and lay the foundation for a category-defining platform
What they're looking for
- Strong software engineering fundamentals — Python, backend frameworks (FastAPI, Flask, etc.), and experience with front-to-back product development
- Experience building and shipping applications that integrate ML/AI systems
- Comfort working across the stack (infra, APIs, data, UI) with a bias toward execution
- Hands-on cloud experience (AWS/GCP/Azure), containerization (Docker), and orchestration (Kubernetes or equivalent)
- Track record of delivering high-impact systems in fast-moving environments (startup or equivalent)
- Mindset: ownership, urgency, and comfort with ambiguity
More about this role
We’re building the first Physics Foundation Model, an AI system that learns from simulation, experiment, and equations to instantly predict and simulate physical behavior.
Our vision is to make the universe computable. Every pattern of nature, every equation, every experiment, instantly at your fingertips.
We’re looking for a Founding SWE who thrives on building systems end-to-end: someone who can take cutting-edge ML models and turn them into production-ready applications, iterate quickly with users, and lay the foundation for a category-defining platform
- Build robust, user-facing systems that expose physics-informed models as real applications.
- Own end-to-end delivery: from prototype → product → production deployment.
- Translate ML research and novel Models into usable, scalable tools
- Design APIs and services that connect training pipelines, inference engines, and customer-facing interfaces.
- Shape the culture, architecture, and trajectory of an early startup.
- Strong software engineering fundamentals — Python, backend frameworks (FastAPI, Flask, etc.), and experience with front-to-back product development.
- Experience building and shipping applications that integrate...
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