Senior Software Engineer, Machine Learning

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

The Role

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 engineer to our team to help us build and release more machine learning-powered value to our users. 

What You'll Do

• Architect, design, and implement high-quality machine learning software applications, infrastructure, and tools.

• Collaborate with machine learning researchers and engineers to implement and deploy algorithms, evaluate model performance and optimize models.

• Work with stakeholders across machine learning and operations teams to iterate on systems design and implement tools to help bring machine learning research to production

• Create re-usable software and systems to accelerate development.

• Profile, tune, and optimize system performance and debug production issues.

• Maintain high standards by participating in reviews, designing for fault tolerance, and creating continuous improvement mechanisms.

What You’ll Bring

• 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.

• Experience with cloud based environments, Kubernetes or Docker, and Infrastructure as Code

• Experience in software design and architecture

• Excellent interpersonal and written communication skills

Ideally, You Have

• 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.

• Experience in evaluating the performance of Machine learning algorithms.

• Demonstrated experience incubating and productionizing new technology, working closely with research scientists and technical teams from idea generation through implementation

• Experience with React.js or other frontend experience is a plus

Why Work at Abridge?

• 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!

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 u