---
title: 'Physics Applications - Software Engineer at Vinci4d'
canonical: 'https://feeny.ai/job/physics-applications-software-engineer-vinci4d-palo-alto-16fk2aesx7bb'
type: 'job'
last_seen: '2026-09-08'
---

# Physics Applications - Software Engineer at Vinci4d

- **Company:** Vinci4d
- **Location:** Palo Alto, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-06-10
- **Last confirmed live:** 2026-09-08
- **Apply:** https://jobs.ashbyhq.com/vinci4d/4c928f3b-37ef-4e48-b306-a5cc99b04c34

## Job description

## THE MISSION

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.

- Trained on PetaBytes of structured physics data
- Running billion-voxel inference in production
- Tier-1 semiconductor and hardware customers
- Operating across multiple physical scales and operator regimes

We are scaling deployment at industrial magnitude:

- Increase simulation throughput by two orders of magnitude
- Expand simulation capabilities to maximize utility and domain coverage
- Support global, multi-entity deployment across Tier-1 ecosystems

Our ambition is to become the default operator intelligence layer that hardware companies run on.

## SOLVING ACROSS SPACE AND TIME

Our proven unified model architecture allows users to rapidly obtain steady state solutions of various partial differential equations. We are expanding this capability to support new physics, new geometries. Beyond that we are building out transient solutions, modeling interactions, deformation and dynamics. A core challenge as we scale out support is designing simple and clean interfaces that turn portions of the codebase into a clean library, ensuring they are correct and accurately reflect the underlying physics being modeled. These are promising applications where Vinci’s approach can not only reduce the compute load but also achieve greater accuracy.

## WHAT YOU WILL DO

Your north star will be production and delivering value to our customers while establishing and maintaining the technical integrity of our codebase.

In this role you will define and implement high-quality, reusable software libraries for our core simulation engine. You will drive code quality, testability, and architectural standards across the team, ensuring our production system scales gracefully and remains maintainable. This includes designing interfaces that are easy to access and correctly reflect the physics they are modeling. You will take ownership of critical system components, mentor junior engineers, and guide the team in transforming research prototypes into hardened, customer-facing features.

You will work with Physicists, AI researchers, Software Engineers and Computational Geometry experts. You will collaborate closely with this team to enforce software engineering best practices throughout the full development lifecycle, from ideation to deployment.

## WHAT WE’RE LOOKING FOR

Qualifications:

- 8+ years of experience in high-quality software development, with significant experience designing and building production-grade systems.
- Prior experience with scientific computing or physics simulators (FEM, FEA, Molecular Dynamics, FDTD), or large-scale machine learning systems.
- STEM MSc, PhD preferred but not required.
- Demonstrated ability to lead technical initiatives focused on code health, modularity, and system correctness.
- Expertise in building robust, tested, and maintainable software libraries and APIs.
- Strong proficiency in modern software development practices, including system design, agentic coding, testing frameworks, and continuous integration/delivery (CI/CD).
- Have contributed to a production data processing system.

We are very excited to talk with you if you have

- Experience building and maintaining core ML, data infrastructure, or numerical computing software (e.g., PyTorch, Numpy, Cuda, distributed systems).
- Experience going from early stage prototype moving to a production environment
- At a Startup or National Lab
- Have leveraged simulation for design or data generation purposes.

## ENGINEERING EXPECTATIONS

- Architectural Leadership: Define and uphold rigorous software design standards to ensure the code base remains clean, modular, and scalable in a production environment.
- Code Health and Testability: Drive strong CI, comprehensive regression testing, and validation discipline across all components.
- Technical Ownership: Capable of independently solving complex architectural problems and taking ownership of core model infrastructure evolution.
- Mentorship: Mentor scientists & engineers on best practices, performance optimization, and system design.

## WHY VINCI

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.

## Our Mission & Impact

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 contribute to expanding our unified model architecture, which currently runs billion-voxel inference, into the transient domain—a key frontier in modeling interactions, deformation, and dynamics. Our ambition is to become the default operator intelligence layer for hardware companies.

Growth & Opportunity

This is a unique opportunity for technical and professional growth, as you will define a foundational abstraction layer early in the company's trajectory. The team is small, friendly, and accessible. You will be empowered to "own and architect large pieces of the system" alongside a team of Physicists, AI researchers, Software Engineers, and Computational Geometry experts. This includes greenfield opportunities to expand Vinci’s core capabilities.

Leadership

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.

## About Vinci4d

## Company Overview
- **One-liner**: Vinci4D builds a physics AI foundation model that enables deterministic, solver-accurate simulation at manufacturing resolution—eliminating meshing, approximations, and customer-specific training.
- **Entity Type**: Private (Series A, 2025)
- **Headquarters**: Palo Alto, California, United States
- **Founded**: 2023
- **Founders**: Dr. Hardik Kabaria (CEO) and Dr. Sarah Osentoski (CTO)

## Core Business
- **Primary industry**: Semiconductor design and simulation; AI-powered physics simulation for hardware engineering.
- **Target customers**: Enterprise (semiconductor and systems companies), B2B.
- **Mission or purpose statement**: Build a physics AI foundation model that natively understands the laws of physics, enabling engineers to innovate at speed and scale once unimaginable.

## Products & Services
- **Vinci Platform**: A physics AI foundation model that performs full-manufacturing-resolution simulations (thermal, thermo-mechanical, warpage) out-of-the-box – no meshing, no approximations, no customer data required. Validated against traditional FEA solvers with <2% deviation and up to 1000× speed improvement. Deployed securely behind customer firewalls.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private company)
- **Key Metric**: Total funding – **$36.5M** (LinkedIn) or **$46M** (conflicting reports per newsroom; includes $36M Series A + $500k seed + possible additional tranche). [getvinci.ai](https://www.getvinci.ai/newsroom/) [linkedin.com](https://www.linkedin.com/company/vinci4d-ai)
- **Notable Investors/Partners**: Khosla Ventures, Eclipse Ventures, Xora. Strategic partnerships with leading semiconductor companies (over half of top 20 semiconductor firms have benchmarked Vinci).
- **Growth Signals**: Employee headcount grew **550% YoY** to 27 people; peer-reviewed validation published at EPTC 2025; 240× to 360× speed improvements demonstrated in customer benchmarks.

## Competitive Advantages
- **Physics-native AI foundation model** that inherently respects governing laws – not a generic LLM.
- **No meshing required** – works directly with native CAD/layout files (OASIS, GDS, IPC-2581) preserving full design fidelity.
- **No customer data needed** – model generalizes out-of-the-box without retraining.
- **Deterministic, solver-accuracy** (<2% deviation from traditional FEA) at 1000× speed, making it production-grade.

## Strategic Focus
- **Current priorities**: Deepen adoption in semiconductor packaging and electronics thermal simulation; expand into adjacent hardware domains (e.g., automotive, aerospace) where full-resolution physics simulation is critical.
- Continue validating through peer-reviewed research and scaling the platform to handle extreme degrees of freedom (100+ million elements).

## Why Work Here
- **Culture**: Founded by AI and simulation experts from Stanford/UC Riverside; team includes world-class simulation engineers and AI researchers (former Carbon, NVIDIA, Zoox engineers).
- **Work environment**: Startup pace with strong research and engineering focus – technical roles dominate (57% of headcount).
- **Funding & stability**: Well-backed by top-tier VCs; runway from $36M+ Series A.
- **Flexibility**: Offices in Palo Alto and Redwood City, CA; not explicitly stated as remote-first, but typical of early-stage deep-tech startups.
- **Engineering culture**: Focus on building a foundation model for physics using Python, PyTorch, CUDA, Kubernetes, Docker, and simulation tools like Ansys Icepak/FloTHERM.

## Sources
1. [getvinci.ai (Home)](https://www.getvinci.ai/)
2. [getvinci.ai (Team)](https://www.getvinci.ai/team/)
3. [getvinci.ai (Newsroom)](https://www.getvinci.ai/newsroom/)
4. [linkedin.com (Company Page)](https://www.linkedin.com/company/vinci4d-ai)
5. [jobs.ashbyhq.com (Careers)](https://jobs.ashbyhq.com/vinci4d)

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