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Develop and productionize machine learning applications for physics simulation, including transient modeling, temporal propagation, geometry meshing, and simulation acceleration. Generate and curate training and verification data, prototype and validate new capabilities, and collaborate with physicists, AI researchers, software engineers, and computational geometry experts to deliver customer-ready solutions. Contribute to production data systems, model infrastructure, testing, validation, and software engineering practices.

Own production release lifecycles and deployment decisions while designing and executing system integration and automated tests. Build Python and Playwright test frameworks for web and physics-AI systems, validate numerical outputs against FEA benchmarks, champion test-driven development, coordinate releases, and translate technical changes into customer-facing release notes.