Software Engineer - Medical Image Reconstruction (C++/CUDA)

About the 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.

Responsibilities

• Contribute to the development of GPU-native CT image-reconstruction platform in C++ and CUDA.
• Implement signal- and image-processing algorithms in efficient, high-performance code.
• Work alongside physicists, algorithm architects, and engineers to develop and optimize CT reconstruction software.
• 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.

Requirements

Required qualifications:

• A bachelor's degree or higher in Computer Science, Electrical or Computer Engineering, Mathematics, Physics, Biomedical Engineering, or a related field.
• 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.
• 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.

Qualifications

Preferred qualifications:

• Experience optimizing code for resource-constrained or embedded environments.
• Background in image or signal processing, including the theory of medical image formation.
• Familiarity with MATLAB or Python.
• Experience with machine learning techniques.

Skills

Desired skills:

• Strong foundation in C++.
• Experience with GPU programming (CUDA, OpenCL, or HIP).
• Proficiency in image or signal processing.
• Knowledge of machine learning techniques.

Benefits

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.

Pay

The pay range for this position in Ohio is $89,000 to $141,000.00. The actual base pay offered may vary within the posted ranges depending on multiple factors including job-related knowledge/skills, experience, business needs, geographical location, and internal equity.

Schedule

This role is a hybrid role with three days in the office and two days remote each week.

Benefits

In addition to a competitive salary, employees are eligible to participate in our comprehensive Philips Total Rewards benefits program, which includes a generous PTO, 401k (up to 7% match), HSA (with company contribution), stock purchase plan, education reimbursement and much more.

Company

We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve.

Philips Transparency Details

Details about our benefits can be found here.

Additional Information

US work authorization is a precondition of employment. The company will not consider candidates who require sponsorship for a work-authorized visa, now or in the future. Company relocation benefits will not be provided for this position. For this position, you must reside in or within commuting distance to Ohio. This requisition is expected to stay active for 45 days but may close earlier if a successful candidate is selected or business necessity dictates. Interested candidates are encouraged to apply as soon as possible to ensure consideration.