Cohere Health
Healthcare
StaffMachineLearningEngineer
“Staff Machine Learning Engineer at Cohere Health. Skills: Machine Learning, Deep Learning, Python, NLP, Cloud Platforms, Production ML Systems. Design, build, and deploy advanced machine learning systems for retrieval, classification, prediction, and generative use cases. Apply advanced statistical and ML techniques to extract insights from large-scale structured and unstructured healthcare datasets”
What You'll Achieve.
Powering and scaling machine learning capabilities within our Intake product; Automate decision-making; Improve data quality; Reduce administrative burden for clinical teams; Deploy production-grade ML systems that directly impact how members and providers experience Cohere Health; Contribute to broader Enterprise ML initiatives; Drive data-informed decision-making; Shape ML strategy and performance tracking across the organization
Industry & Context.
Complex clinical and operational intake workflows; Uncover hidden drivers; Inform strategic decisions; Define problem statements; Forming falsifiable hypotheses; Designing rigorous evaluation frameworks
What They're Looking For.
Must Have
Master's degree in Computer Science, Data Science, Machine Learning, or a closely related quantitative field, 7+ years of professional experience in applied machine learning or data science, Ownership of production ML systems, Deep expertise in Python, Hands-on experience building and deploying deep learning models for NLP tasks, Understanding of experimental design, model evaluation, and optimization for real-world production environments, Experience leveraging cloud platforms across the ML lifecycle (training, deployment, monitoring), Proven ability to collaborate with product, business, and clinical partners to drive data-informed decision-making, Excellent written and verbal communication skills
Nice to Have
PhD preferred, Experience with generative AI, large language models, agentic systems, or Retrieval Augmented Generation (RAG), Experience driving automation in healthcare or regulated environments, Familiarity with healthcare workflows such as claims, coding, utilization management, or network operations, Experience working with unstructured healthcare data (e.g., clinical notes, OCR, document understanding), Hands-on experience with AWS tools such as SageMaker Studio
What You'll Do.
and deploy advanced machine learning systems for retrieval
and generative use cases
Apply advanced statistical and ML techniques to extract insights from large-scale structured and unstructured healthcare datasets
Lead model development across the ML lifecycle
including experimentation
Develop and oversee scalable
reusable codebases and ML infrastructure to support production use cases
Drive experimentation by defining problem statements
forming falsifiable hypotheses
and designing rigorous evaluation frameworks tied to business outcomes
and present ML insights and results to technical and non-technical stakeholders
including executive leadership
Serve as a technical mentor and advisor to junior engineers
Contribute as an expert advisor across multiple initiatives
helping shape ML strategy and performance tracking across the organization
How You'll Work.
Team & Collaboration
Partner closely with clinical operations, product, and engineering teams; Collaborate cross-functionally with product managers, clinicians, data engineers, BI engineers, and design teams; Proven ability to collaborate with product, business, and clinical partners to drive data-informed decision-making; Serve as a technical mentor and advisor to junior engineers; Contribute as an expert advisor across multiple initiatives
Communication Scope
Excellent written and verbal communication skills; Experience presenting to both technical and non-technical audiences
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