Forward Deployed ML Engineer - HealthTech / Series A

This role is for our partner.

[the company] is building the agentic AI layer for oncology EHRs. Cancer hospitals spend billions on highly trained staff manually reading unstructured patient records - pathology reports, clinical notes, genomic panels - to power workflows like trial matching, registry curation, visit prep, and quality reporting. We replace that manual work with task-driven AI agents that sit inside the EMR and process records at scale, in real time. Our platform is trusted by the 4 of the top 10 Best Hospitals for Cancer by U.S.News and several of the largest community practices. We have grown 10x in the last year and process millions of oncology medical documents monthly. Build and deploy AI agent pipelines that extract structured oncology variables from unstructured patient documents. You own the full cycle: understanding the customer's data dictionary, studying the source clinical documents, building extraction agents, evaluating accuracy, deploying to production, and iterating until it works.

Requirements

2+ years building ML/AI in production
Built AI agents or multi-step LLM pipelines
Strong Python
Prompt engineering, fine-tuning, RAG, eval design
Evaluation frameworks for LLM document extraction
Willingness to become oncology-domain expert
Customer-facing comfort
High-intensity delivery sprints

Nice to have: Kept up with agentic ML landscape; clinical or biomedical NLP.
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