
51 - 200 Mitarbeiter
GegrĂĽndet 2018
🏥 Gesundheitswesen
🏠Fertigung
đź”§ Hardware
💰 €25.000.000 Series A im 2021-11
Healthcare • Manufacturing • Hardware
Die Mission von Rad AI ist es, Ärzte mit KI zu unterstützen – damit Zeit eingespart, Burnout reduziert und die Qualität der Patientenversorgung verbessert wird.
đź•’ vor 2 Monaten
🇺🇸 Vereinigte Staaten – Remote
đź’µ $170.000 - $220.000 / Jahr
⏰ Vollzeit
đźź Senior
🧬 Forschungswissenschaftler
🦅 H1B-Visum-Sponsor
đź‘» Geisterscore 7%
🗣️🇺🇸🇬🇧 Englisch erforderlich
Woher diese Stelle stammt
Veröffentlicht auf der Karriereseite von Rad AI, nicht über eine Jobbörse
Von Remote Rocketship zum ersten Mal gesehen vor 2 Monaten
Noch offen auf der Website von Rad AI. GeprĂĽft vor 7 Stunden.

51 - 200 Mitarbeiter
GegrĂĽndet 2018
🏥 Gesundheitswesen
🏠Fertigung
đź”§ Hardware
💰 €25.000.000 Series A im 2021-11
Healthcare • Manufacturing • Hardware
Die Mission von Rad AI ist es, Ärzte mit KI zu unterstützen – damit Zeit eingespart, Burnout reduziert und die Qualität der Patientenversorgung verbessert wird.
• Own a multimodal ML work-stream 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 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 useful in real radiology workflows • Design rigorous evaluations covering clinically meaningful operating points, robustness, calibration, and relevant data slices • Partner with engineering to productionize models, make practical system tradeoffs, and learn from post-launch performance • 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 to technical and clinical partners • Contribute to the research roadmap by identifying promising approaches and sharing learnings • Mentor less experienced researchers and engineers through project collaboration, code and experiment reviews, and technical guidance • Advance a meaningful research track from ideation through production • Establish clinical problem understanding, data and evaluation strategies, reliable models, and learning from real-world use • Serve as a trusted technical partner to research, engineering, product, data, and clinical teams
• Strong applied experience in computer vision, NLP, or deep learning • Track record of independently designing experiments, analyzing results, and turning findings into working systems • Experience owning substantial ML projects across the full lifecycle, from data and modeling through production delivery • Deep hands-on ability in Python and PyTorch • Strong intuition for 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 • Judgment to connect model performance to real user and clinical outcomes • Strong collaboration across research, engineering, product, data, and clinical teams • Clear written and verbal communication, including explaining technical tradeoffs to ML experts and clinical partners • Typically 4+ years of relevant applied ML 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 field • 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 • Authorization to work lawfully in the US
• 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
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