Cohere Health is looking to deploy machine learning models to automate burdensome administrative clinical practices by designing, deploying, and monitoring production models that extract or predict relevant clinical findings from structured and unstructured data sources.
Requirements
- Clear understanding of model building, model maintenance and the measures that optimize models for production use
- Understand experimental design and can independently perform collection, measurement, and interpretation of results
- Expert in Python with experience in deep learning frameworks (e.g., PyTorch)
- Hands on experience building deep learning models (e.g., transformers) for NLP tasks
- Experience with generative AI or Retrieval Augmented Generation (RAG)
- Experience working with unstructured healthcare data (e.g., clinical notes)
- Hands on experience using AWS tools such as SageMaker Studio
Responsibilities
- Design, develop and deploy advanced machine learning algorithms for retrieval, classification and generative use cases.
- Develop reliable and scalable production machine learning systems.
- Write and maintain reusable codebases to perform data preprocessing, model training, evaluation, and deployment
- Provide software and machine learning best practice guidance to junior engineers
- Work cross-functionally with diverse stakeholders, including product managers, clinicians, and technical leadership to align ML solutions with Cohere's core objectives.
Other
- At least 7+ years of experience in applied ML with a masters degree or 5+ years with a PhD, ideally in a senior or lead role in a large technology or healthcare company
- MS or PhD required
- About 20% travel
- Embody our core values and principles
- Diverse, inclusive teams make the most impactful work
