MD-Qualified Research & Development Specialist for AI-assisted Medical Reasoning

Remote Full-time
This position requires an MD and at least 2 years of prior experience as a clinician, to research and develop products for deep clinical decision support using large language models, vector databases, retrieval augmented generation, and probabilistic analysis of medical data. Compensation Starting between $210k-$350k per year plus stock options, depending on experience and your preference of cash vs equity vesting over 5 years, along with healthcare benefits. Raises may also become available with good individual performance or team-wide accomplishments that expand our revenue stream. We also offer a Safe-Harbor 401(k) with the IRS maximum employer matching. Location Berkeley / SF Bay Area. We work together in-person at our office in Berkeley for three days per week, and on other days we have the option of working from the office or from home. Qualifications In this role we need candidates with: • An MD and at least 2 years of clinical experience as a treating physician; • fluency in probabilty and statistics sufficient to write critical evaluations of published medical research, including Bayesian statistics. • Familiarity with industry standards for the handling of electronic medical records, including the transmission, storage, categorization, and presentation of medical information through EHR/EMR systems. • Broad familiarity with clinical diagnostic procedures and philosophies accross a range of medical specialties, and the ability to explain the relevance of those procedures and philosophies to how we handle and analyze medical records. The following are not required, but our team will welcome and make good use of experience with: • medical research, writing, and publication; • healthcare regulatory frameworks; • full-stack web development; • product management; • retrieval-augmented generation (RAG) in software development, including with vector databases; • training, fine-tuning, and evaluating LLMs, and/or development of commercially scaled LLM products; • machine learning interpretability research and/or debugging tools.
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