Senior ML Engineer

Key Skills

Aartificial intelligence, Apache Beam, AWS Sagemaker, Design, Effective communication skills, Kubeflow, Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), PyTorch, RESTful, SPARK Programming, TensorFlow, Writing

Job Description

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, including 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.

Responsibilities:

• 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
• Provide feedback to UX team to change our application workflow to improve AI accuracy

Requirements:

• MS in computer science or data science (or related field); PhD in NLP preferred
• 5+ years experience with MLOps and deploying ML models in production environments
• Demonstrated experience with LLMs, both prompt design and fine-tuning
• Demonstrated 5+ years experience training variety of NLP models
• Demonstrated experience using TensorFlow, PyTorch, Sagemaker, Vertex AI, or related platforms
• Demonstrated experience with LLM fine-tuning, RAG, model distillation, reinforcement learning
• Bonus for Spark, Kubeflow, Apache Beam development experience
• Experience with training Automatic Speech Recognition (ASR) is a plus
• Experience with Electronic Health Records (EHR) is a plus
• Strong written and verbal communication skills
• Experience architecting and building RESTful services
• Ability to learn, evaluate and adopt new technologies

$180,000 - $350,000 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.