Physics Applications - Software Engineer

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, serving tier‑1 semiconductor and hardware customers, and operating across multiple physical scales and operator regimes. 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, drive code quality, testability, and architectural standards, 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. You will work with physicists, AI researchers, software engineers and computational geometry experts, collaborating closely to enforce software engineering best practices throughout the full development lifecycle. 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. Preferred Experience Experience building and maintaining core ML, data infrastructure, or numerical computing software (e.g. PyTorch, NumPy, CUDA, distributed systems). Experience moving from early‑stage prototype to a production environment, at a startup or national lab. Leveraged simulation for design or data generation purposes. Engineering Expectations Architectural leadership: define and uphold rigorous software design standards to keep the code base clean, modular, and scalable. Code health and testability: drive strong CI, comprehensive regression testing, and validation discipline across all components. Technical ownership: independently solve complex architectural problems and take ownership of core model infrastructure evolution. Mentorship: coach scientists and engineers on best practices, performance optimization, and system design. Compensation USD 210,000 – 285,000 annually. #J-18808-Ljbffr Vinci4D.ai