Senior ML Research Scientist

Responsibilities

• Own multimodal machine learning workstreams from problem definition through experimentation, evaluation, deployment, and iteration.
• Translate clinical and product needs into ML objectives, data strategies, model approaches, and success criteria.
• Build and evaluate ML systems using transformers, self-supervised learning, weak supervision, detection, localization, and segmentation.
• Develop systems from image, report, and other clinical data for real radiology workflows.
• Design rigorous evaluations covering clinically meaningful operating points, robustness, calibration, and performance across relevant data slices.
• Partner with engineering to productionize models, make practical system tradeoffs, and assess performance after launch.
• Investigate failure modes including 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 and mentor researchers and engineers.

Requirements

• Strong applied experience in computer vision, NLP, or deep learning, including independently designing experiments, analyzing results, and turning findings into working systems.
• Experience owning substantial ML projects across data, modeling, and production delivery.
• Strong hands-on Python and PyTorch skills, with sound judgment regarding model architecture, data quality, experimentation, and evaluation.
• Experience with modern vision or multimodal techniques such as vision transformers, contrastive learning, masked image modeling, or weak supervision.
• Ability to connect model performance to user and clinical outcomes.
• Strong collaboration and communication skills across research, engineering, product, data, and clinical teams.
• 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

• Medical imaging, radiology, healthcare, or other high-stakes application experience.
• 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 distribution-shift sources.
• Familiarity with clinical validation, FDA or HIPAA considerations, or 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.

Compensation and Benefits

• Salary: $170,000–$220,000 annually.
• Medical, dental, vision, and life insurance.
• HSA with employer match, FSA, and DCFSA.
• 401(k), 11 paid company holidays, flexible PTO, annual company-wide and periodic team offsites, and an annual equipment stipend.