Summary
Apple designs consumer products that touch millions. We change the way that people interact with electronic devices around the world.
Our team is responsible for scaling calibrations and validation of Apple's products to millions of devices while guaranteeing high accuracy. We develop mathematical frameworks and computational algorithms that power product validation before and during New Product Introduction (NPI) and scale to mass production. If you have a strong mathematical foundation and are excited about applying rigorous mathematical techniques to solve real-world imaging and metrology challenges, this role offers the opportunity to impact millions of devices globally.
Description
The role of the Computational Imaging Scientist is to develop and deploy mathematically rigorous systems and algorithms using computational metrology to solve cutting-edge challenges in product design and validation. You will craft and innovate algorithms grounded in solid mathematical foundations—leveraging state-of-the-art computational approaches in geometry, optimization, and inverse problem theory—to enable highly effective measurement and calibration instruments.
This is an opportunity to work at the intersection of pure mathematical theory and practical engineering impact, where your mathematical insight directly influences how millions of devices perform.
What Makes an Ideal Candidate? We're looking for someone who:
Thinks deeply about the mathematical underpinnings of imaging and measurement systems
Enjoys translating elegant mathematical theory into efficient, practical, scalable algorithms—and understands implementation trade-offs (speed, accuracy, memory)
Can lead by combining rigorous mathematical thinking with pragmatic engineering and strong software engineering practices
Has hands-on experience implementing mathematical algorithms efficiently, including optimization, vectorization, and numerical precision considerations
Is passionate about solving complex inverse problems and calibration challenges
Brings both mathematical sophistication and the ability to communicate clearly with engineers and non-specialists
Estimated Travel: Up to 25% international travel
Location: Munich, Germany
Responsibilities
Provide technical leadership and mathematical guidance, fostering a collaborative environment where rigorous mathematical thinking drives innovation
Develop comprehensive mathematical frameworks and validation strategies, designing and executing experiments that rigorously test algorithm performance and conducting sensitivity analyses
Serve as the primary technical contact for internal and cross-functional partners, effectively communicating mathematical concepts, algorithms, and technical progress to diverse audiences
Conduct rigorous trade-off analyses and sensitivity studies between hardware capabilities and algorithmic approaches, using mathematical modeling to optimize system performance
Lead design, development, and optimization of robust algorithmic libraries that implement sophisticated mathematical methods for deployment across multiple products
Drive innovation in computational imaging by exploring and adapting advanced mathematical techniques—such as optimization theory, inverse problem methods, and geometric algorithms—to enhance accuracy and efficiency of calibration and validation systems
Contribute to calibration and measurement science by applying mathematical rigor to hardware-algorithm optimization and developing novel approaches to metrology challenges
Minimum Qualifications
Proficiency in efficient algorithm implementation with C++, Rust, or similar systems languages, with experience optimizing mathematical algorithms for performance, memory efficiency, and numerical stability
Experience with mathematical simulation, modeling, and statistical analysis tools (MATLAB, Python, R, or equivalent), and the ability to transition prototypes from these environments into optimized production code
Familiarity with 3D imaging, display metrology, and computational measurement science
Knowledge of optimization theory, inverse problems, or numerical methods is strongly valued
Experience with computer vision or computational geometry from a mathematical perspective
Preferred Qualifications
Masters or PhD in relevant subject matter
Skilled with optical instrumentation design and development
Interest in multi-vision geometry or computational imaging
Familiarity with numerical libraries and frameworks (e.g., BLAS, Eigen, TensorFlow for numerical work) is a plus
Experience with high-performance computing optimizationsuch as SIMD, parallelization, or GPU acceleration is a plus
Technical lead experience, or an interest to move into this area
At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.