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.
Candidates located in Pittsburgh, San Francisco or New York preferred
From transcribing medical parts of the conversation to delivering key takeaways, our trailblazing work in machine learning research makes the Abridge experience possible. We're currently looking to add a machine learning systems engineer to our team to help us build and release more machine learning-powered value to our users.
Architect, design, and implement high-quality machine learning software applications, infrastructure, and tools.
Lead technical domains starting from the problem definition and technical requirements along with implementation and maintenance
Collaborate with machine learning researchers and engineers to implement and deploy algorithms, such as machine learning models.
Work with stakeholders across machine learning and operations teams to iterate on systems design and implementation.
Create re-usable software and systems to accelerate development.
Profile, tune, and optimize system performance and debug production issues.
Design systems for fault tolerance, scalability, security and continuous improvement.
Bachelor's Degree or greater in Computer Science/Engineering, Statistics, Mathematics, or equivalent.
5+ years of industry software development experience, with a background in design patterns, data structures, and test-driven development.
Proficient in developing production-quality software in languages such as C++, Python, or Java.
Proficient with professional software engineering practices & standard practices for the full software life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
Experience with cloud based environments, Kubernetes or Docker, and Infrastructure as Code (Terraform, etc.)
Experience in software design and architecture for highly available machine learning systems for use cases like inference, evaluation and experimentation.
Excellent understanding of low level operating systems concepts including multi-threading, memory management, networking and storage, performance, and scale
Excellent interpersonal and written communication skills
Experience in one or more relevant technical areas: natural language processing, machine learning, distributed systems, or building infrastructure for engineering/science users.
Expertise in machine learning toolchains and techniques, such as Pytorch or Tensorflow.
Demonstrated experience incubating and productionizing new technology, working closely with research scientists and technical teams from idea generation through implementation.
Be a part of a trailblazing, mission driven organization that uses audio as the wedge to improve the healthcare delivery experience
Unlimited PTO, 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!
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.
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).
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.