At Vinci, we are building the operator intelligence infrastructure that modern hardware programs rely on daily. We have already proven that a single foundation model works out of the box across physics on realistic production workloads.
We are scaling deployment at industrial magnitude:
Our ambition is to become the default operator intelligence layer that hardware companies run on. To get there, we need the backend and infrastructure that lets our research move to production reliably, repeatably, and at scale.
Our unified model architecture delivers steady-state and transient solutions to partial differential equations at production scale. None of that reaches a customer without robust infrastructure underneath it: reproducible builds, automated pipelines, well-provisioned cloud, and code that holds up under load. This role owns that backbone. You will make our systems fast, dependable, and easy for physicists, researchers, and engineers to build on.
Your north star will be production and delivering value to our customers.
Join a rare early-stage startup that has successfully moved a foundational product from research to real-world, production environments, already serving Tier-1 semiconductor and hardware customers.
Vinci is building the operator intelligence infrastructure that modern hardware programs rely on daily. We are scaling our solution to accelerate design validation from hours to seconds. You will build the infrastructure that lets our unified model architecture—currently running billion-voxel inference—scale and expand into the transient domain, a key frontier in modeling interactions, deformation, and dynamics.
This is a unique opportunity for technical and professional growth. You will help define a foundational abstraction layer early in the company’s trajectory. The team is small, friendly, and accessible, and you will be empowered to own and architect large pieces of the system alongside Physicists, AI researchers, Software Engineers, and Computational Geometry experts, including greenfield opportunities to expand Vinci’s core capabilities.
You will work with spectacular technical leaders like CTO Sarah Osentoski and CEO Hardik Kabaria, whose vision is to greatly accelerate physics simulations with ML while retaining solver-grade accuracy.
Vinci is a frontier lab building the foundation model for the physical world. The company is developing deterministic, solver-grounded systems that make physics continuously computable, shifting engineering from episodic simulation to continuous physics infrastructure. Already deployed inside production engineering workflows and running on flagship programs, Vinci operates directly on native design and manufacturing geometry to enable high-fidelity physics reasoning without the traditional burden of manual setup, meshing, and specialist-only access. Rather than functioning as a faster point tool, Vinci changes the operating model of engineering by making physics more available, more repeatable, and more actionable across the organization. Its systems support design, verification, manufacturing, and reliability decisions, helping teams evaluate more scenarios, surface physical risk earlier, and improve engineering leverage without scaling specialist simulation teams linearly. Vinci’s broader aim is to make physics a shared reasoning layer for designing, building, and operating the physical world.
