Sr. Machine Learning Engineer

Job description

Job responsibilities

• Drive the full cycle of medical imaging analysis software development, developing algorithms from R&D concepts into robust, commercial medical device products.
• Design, prototype, and implement advanced computer vision and machine learning algorithms tailored for real-time processing of diverse ultrasound modalities, including EBUS and ultrasound probes.
• Develop specialized algorithms to handle the unique challenges of high-frequency ultrasound data, including speckle reduction, acoustic shadowing mitigation, and temporal tracking across video frames.
• Apply and fine-tune state-of-the-art architectures, including spatio-temporal Vision Transformers (ViTs), recurrent networks, nnU-Net, Graph Neural Network (GNN) and Diffusion models, adapting them for noisy,…
• Architect and execute model deployment pipelines, seamlessly integrating trained models into high-performance C++ production environments, utilizing techniques like quantization, pruning, and hardware acceleration to…
• Support system integration and testing while generating formal design documentation and patent applications.

Job requirements

• MS or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field.
• 5+ years of hands-on industrial experience in algorithm development, with a deep specialization in medical imaging and computer vision.
• Exceptional proficiency in Python and C++, with a deep understanding of modern software component design for production environments.
• Expert knowledge of ML frameworks and software toolkits, including PyTorch, OpenCV, MONAI, ITK, VTK, and model optimization tools such as TensorRT or ONNX.
• Strong domain expertise in ultrasound physics, acoustic image processing, and temporal/video data analysis is highly preferred, especially experience with data from EBUS or high-resolution small-profile transducers.
• Experience with spatiotemporal deep learning architectures and deployment of low-latency real-time applications for ultrasound imaging applications.
• Experience or knowledge of the development of AI/ML features in strict alignment with Good Machine Learning Practice (GMLP) principles, ensuring data representativeness and model transparency.
• A proven track record of shipping commercial AI/ML software products is bonus.