Physics & Optical Simulation Software Engineer

Описание

Our team works at the intersection of machine learning, hardware, and software, creating technologies that reshape how people communicate and experience the world around them. The ML-Physics team builds models that leverage both data-driven learning and deep physical understanding to solve complex sensing and optical measurement challenges.

Responsibilities

• Architect, build, and maintain robust, end-to-end simulation pipelines and scalable developer platforms
• Design modular, high-throughput simulation workflows and infrastructure in Python and modern scientific stacks
• Partner with physicists and optical engineers to translate physical models, wave-propagation algorithms, and numerical solvers into performant, clean software modules
• Optimize simulation frameworks for performance, scalability, data throughput, and maintainability
• Develop verification suites, benchmarking frameworks, and automated regression testing pipelines to validate simulation outputs against ground-truth and physical measurements
• Establish best practices for simulation software: modular packaging, version control, CI/CD, and technical documentation within a research-driven engineering environment

Requirements

• M.Sc. in Computer Science, Software Engineering, Applied Mathematics, Electrical Engineering, Physics, or a related technical field
• 3+ years of professional software development experience focused on building large-scale simulations, scientific computing pipelines, or data-intensive software platforms
• Advanced proficiency in Python, including object-oriented design, performance profiling, and modern package development
• Demonstrated track record of independently learning and mastering unfamiliar technical or scientific domains to deliver innovative solutions
• Strong problem-solving skills and experience architecting large-scale, automated software workflows
• Strong cross-functional collaboration and communication skills in English
• Domain background or foundational understanding of wave optics, ray tracing, electromagnetics, or physical modeling

Nice to have

• Experience with scientific computing libraries and numerical frameworks (e.g., NumPy, SciPy, Numba, CuPy, JAX, or PyTorch)
• Experience designing distributed computing workflows, batch simulation schedulers, or cluster/cloud-based execution engines
• Familiarity with C/C++ integration (e.g., pybind11, Cython) or accelerating simulation kernels via GPU/multithreading
• Experience interfacing with lab measurement infrastructure and validating simulation models against physical laboratory prototypes

We offer

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