Full-Time

Physics Applications Software Engineer

Vinci4d

Vinci4d

11-50 employees

Physics-driven AI for hardware design simulations

Compensation Overview

$210k - $285k/yr

Palo Alto, CA, USA

Hybrid

Hybrid work in Palo Alto is required.

Master's, PhD

Category
Software Engineering (1)
Required Skills
Distributed Systems
Software Testing
CUDA
PyTorch
Machine Learning
REST APIs
NumPy
DevOps
Data Analysis
FEM/FEA

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Requirements
  • At least 8 years of experience in high-quality software development, including significant experience designing and building production-grade systems.
  • Demonstrated ability to lead technical initiatives focused on code health, modularity, and system correctness.
  • Expertise in building robust, tested, and maintainable software libraries and application programming interfaces.
  • Strong proficiency in modern software development practices, including system design, agentic coding, testing frameworks, and continuous integration and delivery.
  • Experience contributing to a production data processing system.
Responsibilities
  • Define and implement high-quality, reusable software libraries for the core simulation engine.
  • Drive code quality, testability, and architectural standards across the team to ensure the production system scales gracefully and remains maintainable.
  • Design interfaces that are easy to access and correctly reflect the physics they model.
  • Take ownership of critical system components.
  • Mentor junior engineers and guide the team in transforming research prototypes into hardened, customer-facing features.
  • Collaborate with physicists, artificial intelligence researchers, software engineers, and computational geometry experts throughout the development lifecycle from ideation to deployment.
  • Define and uphold rigorous software design standards to keep the codebase clean, modular, and scalable in production.
  • Drive continuous integration, comprehensive regression testing, and validation discipline across all components.
  • Independently solve complex architectural problems and take ownership of core model infrastructure evolution.
  • Mentor scientists and engineers on best practices, performance optimization, and system design.
Desired Qualifications
  • A STEM Master of Science or PhD is preferred but not required.
  • Experience with scientific computing or physics simulators such as finite element method, finite element analysis, molecular dynamics, or finite-difference time-domain, or with large-scale machine learning systems.
  • Experience building and maintaining core machine learning, data infrastructure, or numerical computing software such as PyTorch, NumPy, CUDA, or distributed systems.
  • Experience moving an early-stage prototype into a production environment at a startup or national laboratory.
  • Experience leveraging simulation for design or data generation purposes.

Vinci4D provides a physics-driven AI platform to accelerate hardware design and semiconductor simulations by delivering thousand-fold faster, verified results without meshing. Its agentic system blends physics with AI to ensure accuracy and prevent hallucinations, and it runs behind client firewalls with production-ready software that does not require training on customer data. The platform can ingest industry-layout files like OASIS/GDS and resolve nanometer-scale features, enabling engineers to run thousands of simulations to guide design decisions. The goal is to speed up hardware design and improve reliability—especially for electronics thermal management—by delivering simulation software that integrates into engineering teams' workflows and production environments.

Company Size

11-50

Company Stage

Series A

Total Funding

$36.5M

Headquarters

Menlo Park, California

Founded

2023

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Simplify Jobs

Simplify's Take

What believers are saying

  • December 2025 emergence from stealth and $46M funding validate strong investor demand.
  • By February 2026, Vinci4D added thermo-mechanical warpage analysis, broadening monetizable use cases.
  • Deployment claims at three leading manufacturers and three top-20 semiconductor validations support enterprise adoption.

What critics are saying

  • Vinci4D still depends on a narrow semiconductor wedge, with thermal and warpage first.
  • The company's $46M total funding forces rapid enterprise sales before competitors copy its workflow.
  • If top foundries reject black-box AI verification, Vinci4D loses its existential credibility advantage.

What makes Vinci4d unique

  • Vinci4D ships physics-first simulation behind customer firewalls, avoiding proprietary-data training entirely.
  • Its February 2026 warpage module extends one pre-trained model across thermal and mechanical workloads.
  • Benchmarks show 1 GB layout files analyzed in about 30 minutes without meshing.

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Benefits

Hybrid Work Options

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
Business Wire
Feb 24th, 2026
Vinci launches AI-powered thermo-mechanical simulation 1,000x faster than traditional tools

Vinci has launched production-grade thermo-mechanical simulation capability that predicts warpage in hardware designs, built on what it calls the world's first foundation model for physics. The system analyses how hardware bends, twists and deforms under thermal conditions, working directly from full-resolution designs without manual setup. The Palo Alto-based company's platform delivers simulations up to 1,000 times faster than traditional tools whilst maintaining solver-grade accuracy. In production benchmarks, Vinci completed full thermo-mechanical analysis on manufacturing-resolution models in approximately 30 minutes, handling boards up to 100 × 100 centimetres with features down to 20 microns. The pre-trained model runs securely behind customer firewalls without requiring proprietary data training. Over ten semiconductor companies have independently verified Vinci's results against existing finite element analysis solvers and experimental data.

FinSMEs
Dec 3rd, 2025
Vinci Announces $46M in Total Funding

Vinci announces $46M in total funding. Vinci, a Palo Alto, CA-based developer of Physics-Driven AI for hardware design and simulation, emerged from stealth with $46M in total funding. Its Series A round was led by Xora Innovation while its Seed round was led by Eclipse. Founded by Hardik Kabaria and by Sarah Osentoski, Vinci has launched a physics-driven AI system that operates like a team of hardware engineers, running thousands of verified simulations in hours. Vinci's agentic system combines proven physics methods with an AI model to deliver fast simulations. The system is already deployed, powering next-generation design programs at three leading semiconductor manufacturers. Pre-trained and production-ready, it operates securely behind customer firewalls, requires no training on proprietary data and delivers verified results immediately upon deployment.

MarketScreener
Dec 2nd, 2025
Software firm Vinci, which speeds up hardware simulation, raises $36 million

Startup Vinci said on Tuesday it has raised $36 million to finance its business of building software that can speed chip and other hardware design by significantly accelerating the simulation of such...

K5 Global
May 31st, 2024
K5 Global | Companies

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