Principal Machine Learning Engineer, Medical Imaging

Our client is seeking a senior engineer to lead the development of computer vision models for a medical imaging platform. This role combines hands-on model development, technical leadership, and validation work within a regulated product environment.

The engineer will develop algorithms that identify and categorize cells, isolate cellular structures, and translate image-level findings into diagnostic outputs. They will work closely with clinical specialists and engineering teams to deliver accurate, reproducible models suitable for production., * Develop and refine deep learning models for image classification, segmentation, and related prediction tasks.

• Build methods to identify cell boundaries and nuclei, measure cellular characteristics, and process overlapping cells.
• Manage training data preparation, annotation workflows, dataset partitioning, and image preprocessing.
• Address uneven class distributions, differences in staining and imaging conditions, and incomplete labels.
• Establish evaluation methods that measure clinical performance across diagnostic categories.
• Maintain reproducible experiments and prevent data leakage between training and evaluation datasets.
• Collaborate with clinical experts to improve labeling consistency and review challenging cases.
• Prepare technical documentation, testing protocols, and validation results supporting regulated product development.
• Guide engineers on model development practices, code quality, and deployment standards.

• 10+ years of software engineering experience, including at least 5 years developing and deploying deep learning solutions for computer vision.
• Advanced Python skills and strong experience with PyTorch or TensorFlow.
• Hands-on expertise in convolutional neural networks, transfer learning, and image segmentation.
• Experience working with medical or microscopy images, including high-resolution image processing and variation in color or staining.
• Strong understanding of model evaluation, class imbalance, experiment tracking, and reproducible training.
• Ability to communicate technical findings clearly and produce thorough engineering documentation.
• Master’s or doctorate in computer science, engineering, or a related discipline; a bachelor’s degree with equivalent experience will also be considered.

Preferred Experience

• AI development for digital pathology or cell-based imaging.
• Supporting regulatory submissions for medical device software.
• Familiarity with medical device software lifecycle, quality, and risk management standards.
• Image annotation platforms, instance segmentation, and imaging calibration.
• Optimizing models for deployment through quantization or inference acceleration.
• Technical leadership or mentorship of a small engineering team.