Senior Machine Learning Engineer, Platform

About the role

This is a Senior Machine Learning Engineer (Platform) opportunity with a Seed-stage US health data company that runs a patient-powered real-world data platform. It is the first ML hire, owning the technical side of a multi-quarter effort to extract structured features from unstructured clinical text such as notes, discharge summaries, pathology reports and scanned faxes. The work is roughly 70% applied ML on clinical text and 30% LLM-based. The role reports to the Head of Platform Engineering. You’ll own the full model lifecycle from framing and annotation strategy through deployment and retraining, define accuracy targets with stakeholders and build the evaluation harness, and partner with Clinical Data Managers on quality control and human-in-the-loop review. You’ll build clinical NLP pipelines with backend engineers and treat PHI handling, de-identification and audit trails as part of the modelling work. The ideal candidate will have 6+ years in applied ML with models taken to production, and real healthcare or life sciences experience with clinical data, which the posting says is not negotiable. Depth in text extraction, named entity recognition, classification and sequence labelling, practical LLM experience and strong Python fundamentals are expected. Knowledge of clinical terminologies such as SNOMED CT, ICD-10, LOINC and FHIR, and OCR experience, would be advantageous. This is a remote US position. We're looking for someone curious, pragmatic, and eager to work across the stack with a small senior team. You'll own end-to-end delivery of major features, influence architecture, and mentor engineers.

What you'll do

• Ship customer-facing features on a weekly cadence.
• Partner with design and product on scoping and trade-offs.
• Drive technical quality through review, testing, and docs.
• Mentor one or two engineers on your team.

Requirements