---
title: 'Release Manager & QA Engineer at Vinci4d'
canonical: 'https://feeny.ai/job/release-manager-qa-engineer-vinci4d-palo-alto-qmj56s3sc05h'
type: 'job'
last_seen: '2026-09-08'
---

# Release Manager & QA Engineer at Vinci4d

- **Company:** Vinci4d
- **Location:** Palo Alto, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-25
- **Last confirmed live:** 2026-09-08
- **Apply:** https://jobs.ashbyhq.com/vinci4d/5cb9274f-364b-470c-89f8-90c6b453686f

## Job description

## ABOUT US

Vinci is building the intelligence layer for hardware engineering. For decades, physics has been one of the biggest constraints on how physical products get designed — not because engineers don't trust it, but because it's been too slow and too expensive to use continuously. Teams make hundreds of design decisions before they ever see high-fidelity physics; by the time the simulation arrives, the design is largely locked.

We change that. Our Foundation Model for Physics makes deterministic physical reasoning available while a design is still evolving, so engineers can make better decisions before the cost of change compounds. Unlike general-purpose AI, our model learns physical behavior from first principles — not from human-generated text or images.

Today, Vinci is deployed on production engineering programs at leading semiconductor companies — the hardest physics problems in modern electronics. Semiconductors are not the limit. They're the proof: our ambition includes everything downstream of the chip, from robots and vehicles to data centers and aircraft.

We're growing fast, and hiring across the company. Joining now means arriving early enough to help shape how Vinci works, not just what it ships.

## GENERAL DESCRIPTION

As a Release Manager & QA Engineer at Vinci, you will be a primary guardian of our software’s reliability and conductor of our deployment cycles. Because our customers rely on us for critical engineering decisions, your role is pivotal in ensuring our predictions are accurate and our software is stable. Your core focus will be the verification and validation of our AI models and web platform. You will lead System Integration Test design and execution, eventually scaling these through automation, while championing Test-Driven Development across the engineering team. Additionally, you will orchestrate the ‘last mile’ of the delivery process to ensure seamless production releases.

## THE ROLE

- Own the Release Lifecycle: Act as the final gatekeeper for production deployments, managing versioning, coordinating "Go/No-Go" decisions, and overseeing deployment pipelines and customer installations.
- Bridge Engineering & Product: Collaborate with AI/ML experts, thermal/mechanical engineers, and software developers to translate complex technical updates into actionable insights and release notes for both technical and non-technical customers.
- Architect Automated Test Suites: Design and maintain end-to-end automation frameworks (using Python and Playwright) that validate both our web interface and our underlying physics-AI inference engines.
- Validate Numerical Accuracy: Develop specialized testing strategies to compare Vinci’s AI-generated thermal and mechanical results against traditional FEA benchmarks, ensuring high-fidelity outputs.

## QUALIFICATIONS

- Quality Expertise: 6+ years of experience in software quality engineering with a mastery of designing comprehensive test plans. You excel at defining the "what" and "how" of a test suite before any code is written.
- Test Architecture & Logic: The ability to translate complex engineering requirements into structured, unambiguous test logic. You can design clear procedural instructions that serve as a scalable blueprint for both manual execution and automation.
- The "Gatekeeper" Mindset: Exceptional attention to detail and the analytical ability to perform rigorous risk evaluations. You can weigh technical defects against deployment schedules to make informed "Go/No-Go" decisions during fast-paced release cycles.
- CI/CD & DevOps Literacy: Direct experience managing deployments within a Linux/Debian environment using tools such as GitHub Actions, Docker, or Jenkins.

## BONUS QUALIFICATIONS

- Engineering Domain Knowledge: Familiarity with CAD/CAE data formats (GDSII, OASIS, STEP, ECXML, IPC) or basic concepts in thermal/mechanical simulation.
- HPC Experience: Background in testing high-performance computing applications or software that heavily utilizes GPU acceleration.

## WHY JOIN US

- Be part of a team defining the future of AI in hardware design.
- Work at the intersection of advanced AI, real-world engineering, and customer success.
- Collaborate with world-class engineers and researchers in a fast-moving startup environment.

## 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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