Forward Deployed ML Engineer

Responsibilities

• Build and deploy AI agent pipelines to extract structured oncology variables from unstructured patient documents
• Own the full development cycle: studying clinical source documents, building extraction agents, and evaluating accuracy
• Design and implement evaluation frameworks for LLM-based document extraction
• Deploy models to production and iterate based on real-world performance and customer data dictionaries
• Work closely with customers to ensure high-accuracy delivery in high-intensity sprints

Requirements

• 2+ years of experience building ML/AI models in a production environment
• Proven experience building AI agents or multi-step LLM pipelines
• Strong proficiency in Python
• Deep expertise in prompt engineering, fine-tuning, RAG, and evaluation design
• Experience with evaluation frameworks specifically for LLM document extraction
• Comfort in customer-facing roles and a willingness to become an oncology-domain expert

Preferred Qualifications

• Deep knowledge of the current agentic ML landscape
• Experience with clinical or biomedical Natural Language Processing (NLP)

About the Company

Our partner is building the agentic AI layer for oncology EHRs. They replace manual clinical workflows with task-driven AI agents that process pathology reports, clinical notes, and genomic panels at scale. Their platform is trusted by four of the top 10 Best Hospitals for Cancer and processes millions of oncology medical documents monthly.