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Technical Staff Member - High-Performance Sparse Linear Algebra & GPU Solver Architecture

Vinci4DPalo Alto HQ
Hybrid Full-time

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Experience Level

Experience

Qualifications

Qualifications:A Bachelor's degree in Computer Science, Mathematics, or a related field. Experience with numerical methods, particularly in linear algebra and solver architectures. Familiarity with GPU programming and parallel computing. Strong analytical and problem-solving skills.

About the job

Technical Staff Member - High-Performance Sparse Linear Algebra & GPU Solver Architecture

Vinci | Full-Time | Remote / Hybrid

Our Mission

At Vinci, we are pioneering AI-driven infrastructure that empowers modern hardware programs to make precise physics decisions confidently. Our cutting-edge software offers manufacturing-resolution physics simulations with unparalleled accuracy at speeds significantly surpassing traditional tools, eliminating the need for meshing and approximation overhead.

We are actively engaged with a diverse array of Tier-1 partners across semiconductor IDMs, foundries, advanced packaging, fabless companies, automotive, EMS, and energy hardware development. This translates to real solver constraints rather than mere benchmarks, as the simulation decisions we facilitate directly influence tangible hardware outcomes, incorporating a variety of operator structures and conditioning regimes.

We are currently developing the foundational solver architecture designed to scale from billions of degrees of freedom to trillions, ensuring determinism and adaptability across vastly different operator landscapes and distributed environments.

The Challenge Ahead

This position focuses on the core numerical substrate rather than application wrappers. Your tasks will include:

  • Extreme scale conditioning and convergence

  • Domain decomposition and Schwarz theory implementation at production scale

  • Robust multilevel and multigrid preconditioning

  • Development of communication-avoiding Krylov and hierarchical solvers

  • Deterministic parallel reductions across GPU clusters

  • AI-enhanced solver components rooted in numerical precision

Your contributions will be pivotal in shaping the solver architecture that accommodates not just a singular physics model but a comprehensive operator ecosystem, including indefinites, saddle-point systems, significant coefficient jumps, anisotropy, and tightly coupled multiphysics blocks typical in real-world hardware workflows.

Your Contributions

You will take charge of designing and delivering production-ready solver infrastructure, including:

Domain Decomposition & Schwarz Methods

  • Additive and multiplicative Schwarz frameworks

  • Overlapping and non-overlapping strategies

  • Scalable coarse space construction

About Vinci4D

Vinci is at the forefront of AI-driven technology, crafting innovative solutions that allow for high-fidelity physics simulations. Our mission is to redefine how hardware interacts with complex physics through advanced computational methods and collaborative partnerships with industry leaders.

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