Lead Machine Learning Engineer

Health care is all about conversations, with over 2B spoken conversations each year between patients and their care teams in just the United States. However, people forget up to 80% of those conversations, leading to worse patient outcomes. And doctors are burning out writing notes in their EMRs instead of focusing on their patients. That’s where Abridge comes in — our audio-based standalone and integrated solutions record and summarize medical conversations, anywhere care happens.
We're looking for an experienced Machine Learning Engineer to lead a team of ML experts. This role is a combination of managerial responsibility and hands-on applied research. You'll work closely with our product management team to define the roadmap, and will combine research and commercialization activities to keep Abridge at the forefront of medical conversation AI.

Your responsibilities:

• Lead team of machine learning engineers and scientist in performing data preprocessing, define performance measures based on development and test sets.
• Design, develop, and improve complex state-of-the- art speech and language processing (advanced sensing) systems/pipelines for various business requirements using AI and MLOps techniques/tools like Transformers, medical ontologies, Docker, and Kubernetes.
• Develop fast and efficient algorithms to ensure the smooth operation of production-ready software.
• Work with a cross-functional team of engineers, researchers, and designers to understand data-flow and build self-learning systems accordingly.
• Apply subject matter expertise to innovate and create new technology models to increase system stability and robustness.
• Identify problems with the deep learning models environment to anticipate solutions involving the current computer hardware and software.
• Guide stakeholders and customers in the understanding of new system requirements, products and research.
• Maintain and improve AI research standards in the company by implementing best practices in AI research/products like rigorous automatic evaluation, human-centric evaluation, and A/B testing.
• Disseminate research works from the company by publishing them in top-tier academic conferences like AAAI and EMNLP.

Ideally, you:

• Have experience building machine learning-powered software solutions for the health care industry
• Have published multiple papers in the field of automated medical conversation understanding
• Have managed teams of machine learning experts, including overseeing both research and commercialization activities

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.
Principals only, please.
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 believe that "you need to taste good things to have good taste." 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).