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Machine Learning Scientist (All Levels)

Abridge · SF Office

$205k–300k/yr Hybrid
GPUPyTorchTensorFlowDeep learningNLP

ABOUT ABRIDGE Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients. Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems. We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. THE ROLE From transcribing medical conversations to delivering key takeaways, our trailblazing work in machine learning research makes the Abridge experience possible. We're currently looking to hire research scientists with experience in machine learning and natural language processing. The ideal candidate will bring technical mastery, fluency with foundation models, genuine interest in the medical domain, and strong critical thinking skills to the role. At Abridge, all of our ML work has a strong research component, and all of our research scientists contribute directly to real products that impact the lives of doctors. WHAT YOU'LL DO - Advance the state of the art in medical NLP, in areas including conversation summarization, evidence extraction, outcome prediction, evaluation techniques, and experimentation. - Actively contribute to the wider research community by sharing and publishing origi

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