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[Remote] Clinical Imaging & Machine Learning (ML) Validation Specialist

Remote · USA Full-time New today

Note: The job is a remote job and is open to candidates in USA. Dice is the leading career destination for tech experts at every stage of their careers. They are seeking a Clinical Imaging & Machine Learning (ML) Validation Specialist to validate and evaluate machine learning models applied to medical imaging. This role involves collaboration with data scientists, engineers, and clinicians to ensure ML models are accurate and clinically safe for deployment.

Responsibilities

  • Apply deep understanding of clinical imaging workflows (e.g., radiology, pathology, ultrasound, CT, MRI, X-ray) to guide ML validation efforts
  • Interpret imaging data and clinical context to ensure model outputs are clinically meaningful and safe
  • Define clinical use cases, intended use, and relevant performance metrics for ML models
  • Collaborate with clinicians to review model predictions and failure cases
  • Design and execute validation protocols for imaging-based ML/AI models
  • Evaluate model performance using clinically relevant metrics (e.g., sensitivity, specificity, AUC, PPV/NPV, calibration)
  • Perform subgroup and bias analyses (e.g., by age, sex, device, site, pathology prevalence)
  • Assess robustness, generalizability, and edge-case behavior of models
  • Conduct reader studies and human-AI comparison studies when required
  • Oversee curation, quality control, and annotation of medical imaging datasets
  • Define annotation guidelines and ensure inter-reader reliability
  • Work with labeling teams, radiologists, and clinicians to resolve discrepancies
  • Ensure datasets meet clinical, statistical, and regulatory standards
  • Support regulatory submissions (e.g., FDA, CE, UKCA) with validation evidence and documentation
  • Contribute to clinical evaluation reports, performance evaluation plans, and risk management files
  • Ensure compliance with applicable standards (e.g., ISO 13485, ISO 14971, IEC 62304, Good Machine Learning Practice)
  • Participate in audits, design reviews, and post-market surveillance activities
  • Act as a liaison between clinical teams, ML engineers, product managers, and regulatory affairs
  • Translate clinical requirements into technical validation criteria
  • Communicate validation results clearly to both technical and non-technical stakeholders
  • Provide feedback to model development teams for iterative improvement
  • Monitor real-world performance of deployed ML models
  • Investigate performance drift, data shift, and emerging clinical risks
  • Support continuous learning and model update strategies

Skills

  • Advanced degree (Master's or PhD preferred) in: Biomedical Engineering, Medical Physics, Computer Science (with medical imaging focus), Data Science, Radiology / Clinical Sciences, Or a related field
  • 3–7+ years of experience in medical imaging, ML/AI validation, or clinical data analysis
  • Hands-on experience with medical imaging modalities (CT, MRI, X-ray, ultrasound, pathology, etc.)
  • Experience validating ML or AI models in healthcare or regulated environments
  • Familiarity with clinical study design and statistical evaluation
  • Strong understanding of ML concepts and performance evaluation (no need to be a core model developer, but must be fluent)
  • Experience with Python, R, or similar tools for data analysis and validation
  • Familiarity with DICOM, PACS, and medical imaging data formats
  • Knowledge of dataset bias, generalization, and model interpretability
  • Experience with version control, experiment tracking, and documentation
  • Clinical background (e.g., radiologist, pathologist, imaging scientist)
  • Experience with FDA, CE, or other regulatory submissions for AI/ML medical devices
  • Experience conducting reader studies or clinical performance studies
  • Knowledge of health data privacy regulations (HIPAA, GDPR)
  • Familiarity with post-market surveillance and real-world evidence collection

Company Overview

  • Welcome to Jobs via Dice, the go-to destination for discovering the tech jobs you want. It was founded in undefined, and is headquartered in , with a workforce of 0-1 employees. Its website is https://www.dice.com.

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