Senior Machine Learning Engineer (Clinical Team)

Highlights

• Own tissue segmentation models for ultrasound CT clinical analysis layer.
• Retune 2D, 3D volumetric and fusion models as imaging inputs evolve.
• Productionize models into versioned HIPAA-bound service with monitoring.

Ideal candidate

An applied ML builder who thrives moving from open-ended research to rigorous, verifiable clinical models and cares about robust performance across diverse patient anatomy.

Requirements

• Strong applied ML track record architecting, training and evaluating new models from scratch and benchmarking existing models
• Experience with image segmentation (semantic/instance, 2D and ideally 3D/volumetric) robust across diverse patient anatomy
• Comfortable moving between open-ended research iteration and quantifiable, testable models
• Fluent in modern deep-learning tooling (e.g., PyTorch) and current development practices
• Comfortable working under design controls with documentation and verification