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Prenuvo

Whole-body MRI for early disease detection

Senior AI Applied Scientist 2

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeVancouver, BC, CanadaCA$150k - CA$177k /yr

About the Job

Requirements

  • A strong Master of Science or PhD from a top-tier institution in computer science, biomedical engineering, statistics, mathematics, or a related field.
  • At least four academic or industry years of machine learning experience, with a strong publication or applied-research record including at least one first-author work.
  • Expert-level PyTorch proficiency and the ability to write and review production-quality research code.
  • Demonstrated ability to own a model domain end-to-end, including architecting, training, validating, and deploying to a real performance bar, and to design experiments and validation studies independently.
  • Deep fluency in self-supervised learning, including masked image modeling, contrastive learning, JEPA-style methods, knowledge distillation, and large-scale representation learning.
  • Strong command of modern vision and multimodal architectures, including Vision Transformers, multimodal transformers, foundation models, and vision-language models.
  • Experience in medical image analysis, including segmentation, detection, classification, biomarker extraction, and longitudinal modeling, and multimodal fusion of imaging with radiology, clinical, laboratory, and structured patient data.
  • Experience applying generative and agentic AI, including large language model adaptation and workflow orchestration, to healthcare or research applications.
  • Strong collaboration skills across ML Engineering, Product, and Clinical Ops, with high standards for scientific rigor balanced against delivery speed.

Responsibilities

  • Lead development of foundation models and multimodal systems for whole-body MRI, advancing self-supervised and large-scale representation learning across imaging, radiology, laboratory, and longitudinal data.
  • Own experiment design and validation study scoping for the assigned domain, diagnosing failure modes independently.
  • Drive the data quality, annotation criteria, and quality standards the models depend on, engaging directly with clinical framing for the domain.
  • Guide the strategic application of generative and agentic AI, including large language model adaptation and workflow orchestration, to accelerate research and clinical workflows.
  • Contribute modeling approaches that others adopt, and define and execute a research roadmap that advances foundation-model capabilities.
  • Lead clinical review for the assigned domain, partner across clinical, annotation, and ML Engineering, and raise the team's code-quality bar.
  • Deliver production-ready models with documented validation, clinical sign-off, and performance benchmarks, owning the technical narrative for the domain.

Desired Qualifications

  • Experience in body composition, vascular imaging, organ segmentation, or lesion detection.
  • Familiarity with FDA 510(k) submission processes or predicate-based regulatory pathways.
  • Publications in top journals and conferences such as ISMRM, NeurIPS, MICCAI, ICML, and RSNA.
  • Experience with interpretable AI and state-of-the-art AI methods.
  • Prior work in a health tech or clinical AI environment.

About the Company

Prenuvo

Whole-body MRI for early disease detection

Prenuvo provides whole-body MRI scans to help detect over 500 cancers and diseases early. The MRI is radiation-free, non-invasive, takes under an hour, and does not use contrast agents. Customers book online and visit Prenuvo’s scanning centers for a session, paying per scan or via a subscription plan. The scans are designed for proactive health monitoring, especially for health-conscious individuals or those with a family history of disease. The service operates in the preventive medicine and diagnostic imaging space and sells direct-to-consumer scanning services. The goal is to shift healthcare from waiting for symptoms to early detection, which can lead to less invasive treatments and lower long-term costs by catching diseases early.

Company size
201-500
Company stage
Series B
Total funding
$190M
Headquarters
Redwood City, CA
Founded
2018

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