Nabla delivers a unified clinical AI platform used by healthcare organizations across specialties and care settings. The platform includes:
Ambient AI documentation that captures clinical conversations and generates structured notes.
AI-powered dictation and clinical workflow tools embedded directly within EHR systems.
Agentic AI capabilities that support multi-step clinical and administrative tasks.
Enterprise-grade infrastructure built for secure deployment across health systems.
The best of AI at the service of healthcare
Nabla’s phenomenal traction is the result of 3 years of diligent product development.
Led by former Meta AI Research engineers, our team has consistently anticipated how AI can revolutionize healthcare delivery. Our Machine Learning team continually leverages the latest advancements to unlock AI’s full potential in healthcare.
Yann LeCun, Meta’s ex-Chief AI Scientist and Turing award winner, is an advisor to Nabla. He’s now focused on AMI Labs, with whom we have a close partnership.
Engineering at Nabla
Engineering at Nabla is lean, fast-moving, and deeply technical. Our teams span machine learning, native desktop applications, and platform infrastructure to deliver AI into clinical settings reliably and at scale.
At Nabla, product development is led jointly by Engineering and Product and organized into cross-functional squads, each focused on a specific product area. Squads bring together product managers, designers, engineers of different profiles, and domain experts, and operate with a high level of ownership.
As a Full-stack Engineer, you'll join one of these squads and contribute end to end to a specific part of the product.
The technical challenges
- Volumetry and efficiency: We handle more than 2.5 million medical encounters per month. Each one is automatically turned into a clinical note sent to the clinician's patient record system, saving thousands of hours of administrative work and giving healthcare professionals more time for their patients.
- Real-time audio transcription: capturing and streaming audio reliably, from in-person visits as well as video consultations, and turning it into transcripts with very low latency
- Resilience: keeping the product working on weak or unstable networks, with no data lost and no disruption to the clinician
- Healthcare integrations: building robust connections to the third-party medical systems clinicians already rely on.
- Complex AI services: designing and running multi-stage LLM pipelines and agentic workflows at scale, with the reliability and auditability a clinical setting requires