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Jobs at Vinci4D.ai (Now Hiring) — 8 open

Vinci4D.ai logoVinci4D.ai

Software Engineer – Nonlinear Solid Mechanics & High-Performance Computing

Palo Alto, California, United States · Hybrid

$190k–$230k/yr

Senior

About Us At Vinci4d, we are building the next generation of simulation software for thermal, fluid flow, and structural mechanics applications — the kind of tools that change how engineers design products, from the first…

Skills: Nonlinear Solid Mechanics, High-Performance Computing, Finite Element Method, C++, Python

Vinci4D.ai logoVinci4D.ai

Head of Product Marketing

Palo Alto, California, United States · Hybrid

$170k–$240k/yr

Senior+

About Vinci Every physical thing you touch exists because somebody, somewhere, successfully navigated the laws of physics. The chips inside your phone. The vehicles on the road. The factories that make modern life possib…

Skills: Product Marketing, Technical Communication, Market Positioning, Value Proposition Development, Sales Enablement

Vinci4D.ai logoVinci4D.ai

Procedural Data Generation Engineer

Palo Alto, California, United States · Hybrid

$170k–$230k/yr

Senior

About Us Vinci is building physics AI for hardware design. Our models deliver ultrafast, accurate thermal and mechanical simulation and our platform puts that capability in the hands of every hardware engineer, not just …

Skills: Python, Programmatic CAD, Computational Geometry, Physics Simulation, Machine Learning

Vinci4D.ai logoVinci4D.ai

Principal Thermal-Mechanical Engineer - (Munich, Germany)

Munich, Bavaria, Germany · Hybrid

$1/hr–$2/hr

Senior+

About Us We are building Physics AI for hardware design. Our software platform helps hardware designers and physics simulation engineers explore, analyze, and optimize hardware systems, leveraging cutting-edge AI to deli…

Skills: Thermal Management, Mechanical Warpage, Stress Analysis, Reliability Engineering, Python

Vinci4D.ai logoVinci4D.ai

Principal Thermal-Mechanical Engineer (South Korea)

Seoul, South Korea · Hybrid

Senior+

About Us We are building Physics AI for hardware design. Our software platform helps hardware designers and physics simulation engineers explore, analyze, and optimize hardware systems, leveraging cutting-edge AI to deli…

Skills: Thermal Management, Mechanical Warpage, Stress and Reliability Analysis, Python, C++

Vinci4D.ai logoVinci4D.ai

Principal Thermal-Mechanical Engineer (Taiwan)

Taiwan · Hybrid

Senior+

About Us We are building Physics AI for hardware design. Our software platform helps hardware designers and physics simulation engineers explore, analyze, and optimize hardware systems, leveraging cutting-edge AI to deli…

Skills: Thermal Management, Mechanical Warpage, Stress Analysis, Reliability Engineering, Python

Vinci4D.ai logoVinci4D.ai

Principal Thermal-Mechanical Engineer (Singapore)

Singapore, Singapore · Hybrid

$1/hr–$2/hr

Senior+

About Us We are building Physics AI for hardware design. Our software platform helps hardware designers and physics simulation engineers explore, analyze, and optimize hardware systems, leveraging cutting-edge AI to deli…

Skills: Thermal Management, Mechanical Warpage, Stress Analysis, Reliability Engineering, Python

Vinci4D.ai logoVinci4D.ai

Physics Applications - Researcher

Palo Alto, California, United States · Hybrid

$190k–$260k/yr

Mid level

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 rea…

Skills: Physics Simulation, Machine Learning, PyTorch, Numpy, Cuda

Vinci4D.ai logo

Software Engineer – Nonlinear Solid Mechanics & High-Performance Computing

Vinci4D.ai

Palo Alto, California, United States • Hybrid

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Senior

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  • $190k–$230k/yr
  • Full-time
  • Competitive Compensation, Equity Participation, Flexible Work Environment
  • Posted 4d ago
  • ~40 hrs/week

Responsibilities

Design and implement high-performance nonlinear solvers for solid mechanics, focusing on geometric and material nonlinearity. Develop and optimize GPU-accelerated linear algebra and FEM discretizations while contributing to the company's CI/CD infrastructure.

Requirements

Requires 3-6 years of experience in computational mechanics or HPC with strong proficiency in C++, Python, and GPU programming (CUDA/HIP). Candidates must have a deep understanding of FEM, iterative solvers, and professional software engineering practices.

Full job description

About Us

At Vinci4d, we are building the next generation of simulation software for thermal, fluid flow, and structural mechanics applications — the kind of tools that change how engineers design products, from the first mesh to the final answer. We are a small, technically deep team that moves fast, ships real software, and takes on hard problems that matter. If you want your work to be foundational to a platform used by engineers worldwide, this is the place.

The Role

We are looking for a software engineer who lives at the intersection of computational solid mechanics, numerical methods, and high-performance computing. You will design, implement, and tune solvers for geometric and material nonlinearity in solid mechanics — think large-deformation, contact, and history-dependent material response — that run at scale on modern hardware. You will write production-quality code, contribute to our CI/CD infrastructure, and collaborate closely with a multi-disciplinary team of physicists, engineers, and software developers.

This is not a "maintain the existing stack" role. You will be building things that don't exist yet, solving problems that require both rigorous mathematical thinking and solid engineering instincts.

What You Will Work On

  • Develop and tune nonlinear solvers for solid mechanics, handling both geometric nonlinearity (large deformation, finite strain) and material nonlinearity (plasticity, viscoelasticity, temperature-dependent and history-dependent constitutive models)

  • Build and optimize the underlying linear algebra: iterative linear solvers and preconditioners for the large sparse systems arising at each Newton iteration

  • Port and optimize these solvers for GPU execution using CUDA, HIP, or equivalent frameworks, with a focus on memory bandwidth, occupancy, and scalability

  • Implement FEM discretizations for structural and thermomechanical field solves, with attention to robustness and convergence under stiff, ill-conditioned, and near-singular conditions

  • Contribute to a robust software engineering foundation: version control discipline, automated testing, CI/CD pipelines, and code review practices

  • Collaborate with domain experts to translate physical models and mathematical formulations into correct, efficient implementations

  • Profile and benchmark solver performance; identify and eliminate bottlenecks

What We Are Looking For

Technical Skills

  • Hands-on experience developing solvers for geometric and material nonlinearity in solid mechanics — large-deformation kinematics, nonlinear constitutive models, and the Newton-type schemes that drive them to convergence

  • Strong foundation in the finite element method (FEM) for solid and structural mechanics

  • Deep familiarity with iterative linear solvers (e.g., Krylov methods) and preconditioning techniques for large, sparse systems, with hands-on experience implementing these inside a nonlinear solver

  • Proven GPU programming experience (CUDA, HIP, SYCL, or similar) with a track record of getting real performance out of hardware

  • Proficiency in C++ and/or Python; comfort working in performance-critical codebases

  • Strong software engineering practices: Git workflows, code review, automated testing (unit, integration, regression), and CI/CD pipelines

Experience

  • 3–6 years of industry or research experience in a relevant field (computational mechanics, scientific computing, computational physics, numerical simulation, or HPC)

  • A portfolio of work — open source contributions, published code, or shipped products — that demonstrates the above

Soft Skills

  • A genuine collaborator: you learn from teammates as readily as you help them

  • Able to communicate technical depth clearly to people from different disciplines — physicists, mechanical engineers, product managers

  • Comfortable with ambiguity and excited by the challenges that come with building something new

  • Self-directed and ownership-oriented: you drive your work to completion without needing to be managed closely

Nice to Have

  • Experience with warpage and residual-stress problems in semiconductor manufacturing (e.g., packaging, die/substrate stacks, thermomechanical deformation)

  • Familiarity with matrix-free methods for nonlinear and linear operator application

  • Experience with geometric multigrid approaches as solvers or preconditioners

  • Background in adaptive mesh refinement (AMR)

  • Familiarity with embedded geometry or immersed boundary methods for solid mechanics

  • Experience applying machine learning to solid mechanics problems (surrogates, constitutive modeling, solver acceleration)

  • Experience with performance profiling tools (Nsight, VTune, Roofline analysis)

Why Vinci4d

  • Work on genuinely hard technical problems with real engineering impact

  • Join a small team where your contributions are visible and your voice is heard

  • Competitive compensation with equity participation

  • Flexible work environment

  • The satisfaction of building something from the ground up — and the opportunity to help define what it becomes

Related keywords

Nonlinear Solid MechanicsHPCFEMCUDAHIPSYCLC++PythonKrylov MethodsNewton-type SchemesLarge DeformationPlasticityViscoelasticityCI/CDGitSparse Systems

About Vinci4D.ai

LinkedInVisit site

A frontier lab building the foundation model for the physical world, already deployed in flagship engineering programs.

Industry
Technology, Information and Internet
Company size
51-200 employees
Founded
2023
Headquarters
Palo Alto, California
LinkedIn followers
5,407

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.

Offices: 316 High St, Palo Alto, California 94301, US

View all jobs at Vinci4D.ai

About Vinci4D.ai

LinkedInVisit site

A frontier lab building the foundation model for the physical world, already deployed in flagship engineering programs.

Industry
Technology, Information and Internet
Company size
51-200 employees
Founded
2023
Headquarters
Palo Alto, California
LinkedIn followers
5,407

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.

Offices: 316 High St, Palo Alto, California 94301, US

View all jobs at Vinci4D.ai

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