Physics & Optical Simulation Software Engineer - Q

Our team is new, growing, and evolving quickly, and we are hiring across multiple disciplines. We work at the intersection of machine learning, hardware, and software, creating technologies that reshape how people communicate and experience the world around them in everyday life.

Apple designs consumer electronics that have touched millions and changed the way people interact with electronic devices around the world. The ML-Physics team works at the intersection of machine learning and physics, building models that leverage both data-driven learning and deep physical understanding to solve complex sensing and optical measurement challenges. We are looking for a Physics & Optical Simulation Software Engineer to build and scale the simulation platforms and data pipelines that power our physical modeling and sensor research. While the domain involves physics and optics, this is a software-first role: you will architect modular, high-throughput simulation systems that turn theoretical formulations into production-grade software tools. We value strong software engineering discipline, expertise in Python, and the intellectual agility to quickly master new scientific domains and innovate.

Minimum Qualifications

• 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 solution
• Strong problem-solving skills and experience architecting large-scale, automated software workflows
• Strong cross-functional collaboration and communication skills in English

Preferred Qualifications

• Domain background or foundational understanding of wave optics, ray tracing, electromagnetics, or physical modeling
• 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