Senior ML Research Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of a multimodal machine learning work-stream, guiding it from problem identification through experimentation, assessment, deployment, and refinement.

• Convert clinical and product requirements into machine learning objectives, data strategies, model methodologies, and success metrics.

• Construct and assess contemporary machine learning systems, encompassing transformers, self-supervised learning, weak supervision, detection, localization, and segmentation.

• Collaborate with image, report, and other clinical data to create systems that are applicable to real radiology workflows.

• Develop thorough evaluations that address clinically significant operating points, robustness, calibration, and pertinent data segments.

• Work alongside engineering teams to implement models in production, navigate practical system trade-offs, and learn from post-launch performance insights.

• Explore failure modes such as laterality errors, inadequate image or report grounding, hallucination, dataset bias, domain shifts, and workflow interruptions.

• Present research results and technical decisions through design documents, experiment reviews, and presentations to both technical and clinical stakeholders.

• Contribute to the research agenda by pinpointing promising methodologies and disseminating insights.

• Guide less experienced researchers and engineers through project collaboration, code and experiment assessments, and technical mentorship.

• Foster a significant research trajectory from concept through production.

• Establish a comprehensive understanding of clinical problems, data and evaluation strategies, dependable models, and insights derived from real-world applications.

• Act as a dependable technical partner to research, engineering, product, data, and clinical teams.

⛳️ Requirements

• Proven applied experience in computer vision, natural language processing, or deep learning.

• A history of independently designing experiments, analyzing the outcomes, and translating discoveries into functional systems.

• Experience in managing significant machine learning projects throughout their entire lifecycle, from data handling and modeling to production deployment.

• Strong practical expertise in Python and PyTorch.

• A solid understanding of model architecture, data quality, experimentation, and evaluation techniques.

• Familiarity with contemporary vision or multimodal methodologies such as vision transformers, contrastive learning, masked image modeling, or weak supervision.

• Ability to relate model performance to actual user and clinical outcomes.

• Excellent collaboration skills across research, engineering, product, data, and clinical teams.

• Clear written and verbal communication skills, including the ability to convey technical trade-offs to both machine learning specialists and clinical partners.

• Typically 4+ years of relevant applied machine learning research or engineering experience, or equivalent scope and impact.

• An MS, PhD, or equivalent practical experience in Computer Science, Electrical Engineering, Machine Learning, Biomedical Engineering, or a related quantitative discipline.

• Experience in medical imaging, radiology, healthcare, or another critical application area.

• Knowledge of chest X-ray, CT, MRI, mammography, or other clinical imaging modalities.

• Familiarity with DICOM, image-report pairing, medical data de-identification, radiology workflows, or clinically derived labels.

• Experience in evaluating models across patients, sites, scanner vendors, protocols, or other sources of distribution shifts.

• Understanding of clinical validation, FDA or HIPAA considerations, or other regulated and privacy-sensitive contexts.

• Experience with 3D vision, longitudinal imaging, report generation, or clinical decision support systems.

• Publications, open-source contributions, or other indicators of research credibility.

• Authorization to work legally in the US.

🏝️ 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.

• Equity.