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Job description
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.
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.