About the role
Responsibilities:
- Design, build, and optimize imaging algorithms for image segmentation, classification, and enhancement (e. g., tissue specimen analysis on glass slides and whole slide images).
- Apply a strong understanding of color spaces (RGB, HSV, LAB, etc. ) to improve image processing pipelines.
- Collaborate with the image quality evaluation team to continuously improve WSI scan quality across diverse specimen types.
- Develop and maintain end-to-end algorithm models for imaging parameters and acquisition sequences, enabling intelligent, content-aware imaging routines.
- Partner with platform and software engineers to co-optimize algorithms and production software implementations.
- Mentor and guide junior engineers in image processing and analytics best practices.
Requirements:
- Bachelor's degree in computer science, information science, or a related field with emphasis on image or signal processing.
- Proven hands-on experience delivering at least one full R& D cycle, transitioning image acquisition and processing pipelines into production platforms.
- Strong knowledge of image processing algorithms, color spaces, and image quality challenges.
- Solid foundation in mathematics, including probability, algebra, and calculus.
- Excellent programming skills in C/C++ and Python; hands-on experience with machine learning libraries is essential.
- Understanding of sensor and camera component interactions within imaging systems.
What Will Make You Stand Out:
- Strong background in image processing, optics, or signal processing.
- Demonstrated innovation through patents, publications, or impactful research contributions.
- Hands-on experience with deep learning frameworks and neural network architectures.
- Experience with compute engines and tools for graphics, computer vision, and ML/AI workloads.
- Solid understanding of statistical modeling, probability theory, and stochastic methods.