Job Title
Job Description
Here at Philips you will continue your engineering career on a team building the GPU-native software that turns raw CT physics into life-saving images inside Philips scanners worldwide, learning to wring maximum performance from constrained hardware at the frontier of C++, CUDA, and AI alongside world-class physicists.
Your role:
- Contribute to our next generation, GPU-native CT image-reconstruction platform in C++ and CUDA, working under the guidance of senior engineers.
- Work alongside physicists, algorithm architects, and engineers to implement signal- and image-processing algorithms in efficient, high-performance code.
- Write, test, document, and maintain software as part of an industry-leading CT reconstruction platform.
- Grow your skills in performance engineering and applied AI, learning to optimize memory use across caches and shared memory, using AI-assisted tools, and exploring how learned models can approximate expensive physics with fast, accurate equivalents.
- This hybrid role is based in Cleveland, OH, with three flexible days in the office and two remote days each week. Regular travel is not typically required.
You're the right fit if:
- You have a bachelor's degree or higher in Computer Science, Electrical or Computer Engineering, Mathematics, Physics, Biomedical Engineering, or a related field.
- You have a strong foundation in C++, whether from professional experience, internships, co-ops, or graduation from a program that teaches computer science in C++. Prior work experience is preferred but not required, and you are eager to deepen your skills.
- Exposure to GPU programming (CUDA, OpenCL, or HIP) is a plus, and experience optimizing code for resource-constrained or embedded environments translates directly, but a genuine eagerness to learn GPU-centric development matters most. You are excited by performance and curious about profiling, parallelization, and getting the most out of modern GPUs.
- You bring a strong mathematical foundation, such as linear algebra, calculus, or numerical methods, which is the quality that matters most for this work. A background in image or signal processing, including the theory of medical image formation, is a plus, and familiarity with MATLAB or Python is helpful. Curiosity about applying machine learning to accelerate scientific or physics computation is also a plus.
- You must be able to successfully perform the following minimum Physical, Cognitive and Environmental job requirements with or without accommodation for this position .
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