Augmedix (Nasdaq: AUGX) delivers industry-leading, ambient medical documentation and data solutions to healthcare systems, physician practices, hospitals, and telemedicine practitioners.
Augmedix is on a mission to help clinicians and patients form a human connection by seamlessly integrating our technology at the point of care. Augmedix’s proprietary platform digitizes natural clinician-patient conversations, which are converted into comprehensive medical notes and structured data in real time. The company’s platform uses automatic speech recognition, and natural language processing, including large language models, to generate accurate and timely medical notes that are transferred into the EHR.
Augmedix’s products relieve clinicians of administrative burden, in turn, reducing burnout, increasing clinician efficiency and improving patient access. Through Augmedix’s proprietary platform and bi-directional communication channel, Augmedix is ideally suited to serve as the vehicle for change at the point of care.
Augmedix is headquartered in San Francisco, CA, with offices around the world. To learn more, visit www.augmedix.com.
About the Role:
The Senior Machine Learning Engineer will build and deploy NLP models and LLMs to understand patient-doctor conversations, identify relevant medical terminology and phrases. This information will be used to build ML-based services and applications that will enable doctors and clinicians to be more efficient and to recommend actions on how to improve patient health.
- Build NLP models using audio clips, transcriptions, patient responses, notes
- Designing, development and deployment of custom LLMs
- Improve processes and tools to generate ground truth for building models
- Deploy models in production at scale
- Build ML pipelines to automate model serving steps
- Work with product team to brainstorm new areas for AI within our product capabilities
- Work with UX team to change our application UI to improve AI accuracy
- MS in computer science or data science (or related field)
- 3 - 5 years experience deploying ML models in production environments
- 3 - 5 years experience developing enterprise software
- Demonstrated experience with generative LLMs
- 2+ years experience building NLP models
- Demonstrated experience using TensorFlow, PyTorch, Sagemaker, Vertex AI, or related platforms
- Bonus for Spark, Kubeflow, Apache Beam development experience
- Experience with Electronic Health Records - EHR - is a plus
- Experience with Automatic Speech Recognition - ASR is a plus
- Strong written and verbal communication skills
- Experience architecting and building RESTful services
- Ability to learn, evaluate and adopt new technologies
$100,000 - $150,000 a year
Salary range is listed above. There are several factors that determine final pay for a position including location and experience. Total compensation will typically include salary + performance bonus + equity.