Senior Machine Learning Engineer Clinical Team

You will own tissue-class segmentation and labeling models for ultrasound CT clinical analysis. You will adapt models across 2D, 3D, and fused inputs; define training and evaluation pipelines; coordinate labeling specifications and dataset quality; and deploy versioned HIPAA-bound analysis services with low-latency inference, confidence estimates, drift monitoring, and safe fallbacks.

Responsibilities

• Own tissue-class segmentation and labeling models for ultrasound CT clinical analysis
• Retune models across 2D, 3D volumetric, and 2D by 3D fusion inputs
• Define training and evaluation pipelines, datasets, and metrics
• Coordinate labeling specifications, quality control, and dataset versioning with contractors, clinicians, and cloud or data partners
• Productionize models into versioned HIPAA-bound analysis services with reproducible inference, confidence estimates, drift monitoring, and safe fallbacks

Requirements

• Applied machine learning model development, training, and evaluation
• Image segmentation including semantic or instance segmentation
• 2D and 3D or volumetric imaging
• Deep-learning tooling such as PyTorch
• Design controls and model documentation and verification