AI / ML & Computer Vision Resource

Role: AI / ML & Computer Vision Resource

Location: Irvine, California · On-site

Role overview

The AI / ML & Computer Vision Resource will develop and validate deep-learning models for cardiovascular medical-imaging use cases. The role will improve model performance and generalizability, explore foundation-model approaches, and partner with clinical, engineering, quality, and regulatory teams to support safe, documented delivery into regulated healthcare settings.

Key responsibilities

• Design, train, fine-tune, and validate deep-learning models for imaging tasks such as segmentation, landmark detection, measurement, and screening.
• Evaluate and improve robustness across imaging vendors, acquisition protocols, institutions, and datasets; optimize accuracy, efficiency, and scalability.
• Advance medical-imaging foundation models and assess supervised, self-supervised, transfer-learning, and other relevant approaches.
• Partner with clinical, engineering, quality, and regulatory teams on verification, validation, bias assessment, risk management, and documentation.
• Build data pipelines and MLOps practices for deployment and performance-drift monitoring; maintain model documentation from prototype through production.

Experience and capabilities

• Strong experience in machine learning, deep learning, and computer vision, preferably involving medical images.
• Practical capability in model training, fine-tuning, validation, and evaluation across varied datasets and acquisition conditions.
• Familiarity with data pipelines, production ML practices, and model-performance monitoring.
• Ability to collaborate on clinical validation, bias, risk, quality, and regulatory documentation for healthcare applications.
• Strong experimental design, technical documentation, and cross-functional communication skills.

Desired outcomes

Validated, well-documented imaging models with demonstrated robustness and a clear path from research prototype to monitored production use.