Senior ML Research Scientist

The role

You will own a multimodal ML work-stream from problem definition through deployment and iteration. You will build and evaluate modern ML systems using image, report, and clinical data.

What you will do

• Own a multimodal ML work-stream from problem definition through experimentation, evaluation, deployment, and iteration.
• Translate clinical and product needs into clear ML objectives, data strategies, model approaches, and success criteria.
• Build and evaluate modern ML systems, including transformers, self-supervised learning, weak supervision, detection, localization, and segmentation.
• Work with image, report, and other clinical data to develop systems that are useful in real radiology workflows.
• Design rigorous evaluations including clinically meaningful operating points, robustness, calibration, and performance across relevant data slices.
• Partner with engineering to productionize models and make practical system tradeoffs.
• Investigate failure modes such as laterality errors, poor image or report grounding, hallucination, dataset bias, domain shift, and workflow disruption.
• Communicate research findings and technical decisions through design documents, experiment reviews, and presentations.
• Contribute to the research roadmap by identifying promising approaches.
• Mentor less experienced researchers and engineers through project collaboration, code and experiment reviews, and technical guidance.

Required qualifications

• Strong applied experience in computer vision, NLP, or deep learning.
• Experience owning substantial ML projects across the full lifecycle.
• Deep hands-on ability in Python and PyTorch.
• Experience with modern vision or multimodal techniques such as vision transformers, contrastive learning, masked image modeling, or weak supervision.
• The judgment to connect model performance to real user and clinical outcomes.
• Strong collaboration skills across research, engineering, product, data, and clinical teams.
• Clear written and verbal communication.
• Typically 4+ years of relevant applied ML research or engineering experience, or equivalent scope and impact.
• MS, PhD, or equivalent practical experience in Computer Science, Electrical Engineering, Machine Learning, Biomedical Engineering, or a related quantitative field.

Nice to have

• Experience with medical imaging, radiology, healthcare, or another high-stakes application area.
• Familiarity with chest X-ray, CT, MRI, mammography, or other clinical imaging modalities.
• Experience with DICOM, image-report pairing, medical data de-identification, radiology workflows, or clinically derived labels.
• Experience evaluating models across patients, sites, scanner vendors, protocols, or other sources of distribution shift.
• Familiarity with clinical validation, FDA or HIPAA considerations, or other regulated and privacy-sensitive environments.
• Experience with 3D vision, longitudinal imaging, report generation, or clinical decision support.
• Publications, open-source contributions, or other evidence of research credibility.

Benefits

• Comprehensive Medical, Dental, Vision & Life insurance
• HSA (with employer match), FSA, & DCFSA
• 401(k)
• 11 Paid Company Holidays
• Flexible PTO policy
• Annual company-wide offsite
• Periodic team offsites
• Annual equipment stipend

About the company

Rad AI is on a mission to transform healthcare with artificial intelligence. Their AI-driven solutions are revolutionizing radiology by saving time, reducing burnout, and improving patient care.