Staff / Senior Software Engineer, ML Systems

at  Abridge

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 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.
• 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.