Machine Learning Science Manager - Abridge|Meet.jobs

薪資

250k - 300k USD Annually

技能需求

    工作機會描述

    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.

    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 an ML Science Manager to lead and manage a team of applied scientists with experience in machine learning and natural language processing and a passion for developing technology to solve both clinical and administrative problems in the medical domain. The ideal candidate will bring technical mastery, fluency with statistics and deep learning (including foundation models), a 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

    • Lead and Manage Research Team: Oversee a team of research scientists, providing guidance, mentorship, and support to foster their growth and ensure the success of research projects.

    • Advance Medical NLP: Drive the advancement of the state of the art in medical NLP, focusing on areas such as conversation summarization, evidence extraction, outcome prediction, evaluation techniques, and experimentation.

    • Contribute Research: Actively contribute to the wider research community by sharing and publishing original research, and encourage team members to do the same.

    • Define and Develop Solutions: Collaborate with the team to define important problems, identify appropriate baselines, develop state-of-the-art methods, and integrate them into production.

    • Incorporate Feedback: Engage with clinicians to gather real-time feedback, guiding further refinements and innovations in our products.

    • Results-Oriented Approach: Maintain a focus on results in the face of ambiguous problems and uncertain outcomes, ensuring that research initiatives have a tangible impact.

    What You'll Bring

    • Demonstrated through papers and (most likely but not necessarily) advanced graduate degrees in, Computer Science, Electrical Engineering, Mathematics, or equivalent experience.

    • Proven track record of high-impact publications at peer-reviewed AI conferences (e.g. *CL, NeurIPS, ICML, ICLR).

    • Significant contributions to open source and deployed technology, showcasing the real-world impact of your work.

    • Demonstrated ability to lead and manage a team, providing both technical and professional guidance.

    • Strong programming skills with proven experience crafting, prototyping, and delivering machine learning solutions into production.

    • Experience with deep learning libraries (e.g. PyTorch, Jax, Tensorflow) and platforms, multi-GPU training, and statistical analyses of observational and experimental data.

    Base Salary: $250,000 USD - $300,000+ USD per year + Equity

    The salary range provided is based on transparent pay guidelines and is an estimate for candidates residing in the San Francisco and New York City metro areas. The actual base salary will vary depending on the candidate's location, relevant experience, skills, qualifications, and other job-related factors. Additionally, this role may include the opportunity to participate in a company stock option plan as part of the total compensation package.

    Candidates willing to work from our SF or NYC offices 2-3x/week preferred (Relocation assistance is available for candidates planning to move to San Francisco or New York)

    Strong preference for candidates who are currently in the San Francisco Bay Area or the New York Tri-State area, or are willing to relocate to these areas. This position requires a commitment to a hybrid work model, with the expectation of coming into the office 2-3 times per week.

    Must be willing to travel up to 10%

    Abridge typically hosts a three-day builder team retreat every 3-6 months. These retreats often feature internal hackathons, collaborative project sessions, and social events that allow the team to connect in person.

    We value people who want to learn new things, and we know that great team members might not perfectly match a job description. If you’re interested in the role but aren’t sure whether or not you’re a good fit, we’d still like to hear from you.

    Why Work at Abridge?

    • Be a part of a trailblazing, mission-driven organization that is powering deeper understanding in healthcare through AI.

    • Unlimited PTO for salaried team members, plus 12 national holidays

    • Comprehensive and generous benefits package:

    • 16 weeks paid parental leave, for all employees

    • Flexible working hours — we care more about what you accomplish than what specific hours you’re working

    • Remote work environment

    • Equity for all new employees

    • Generous equipment budget for your home office setup ($1600)

    • Opportunity to work and grow with talented individuals, and have ownership and impact at a high growth startup.

    • Plus much more!

    Life at Abridge

    At Abridge, we’re driven by our mission to bring understanding and follow-through to every medical conversation. Our culture is founded on doing things the “inverse” way in a legacy system—focusing on patients, instead of the system; focusing on outcomes, instead of billing; and focusing on the end-user experience, instead of a hospital administrator's mandate.

    Abridgers are engineers, scientists, designers, and health policy experts from a diverse set of backgrounds—an experiment in alchemy that helps us transform an industry dominated by EHRs and enterprise into a consumer-driven experience, one recording at a time. We believe in strong ideas, loosely held, and place a high premium on a growth mindset. We push each other to grow and expose each other to the latest in our respective fields. Whether it’s holding a PhD-level deep dive into understanding fairness and underlying bias in machine learning models, debating the merits of a Scandinavian design philosophy in our UI/UX, or writing responses for Medicare rules to influence U.S. health policy, we prioritize sharing our findings across the team and helping each other be successful.

    Diversity & Inclusion

    Abridge is an equal opportunity employer. Diversity and inclusion is at the core of what we do. We actively welcome applicants from all backgrounds (including but not limited to race, gender, educational background, and sexual orientation).

    Staying Safe - Protect Yourself From Recruitment Fraud

    We are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article. Please exercise caution and cease communications if something feels suspicious about your interactions.

    Abridge