[Hiring] Senior Machine Learning Engineer @Novellia

Role Description

Most of what matters in a health record isn't in a structured field - it's in the note, the discharge summary, the pathology report, the scanned fax. Turning that unstructured clinical text into trustworthy, structured features is what makes a longitudinal health history usable for research, and it's one of the highest-leverage capabilities Novellia can own.

You'll be our first ML hire, joining Platform Engineering and reporting to the Head of Platform Engineering, as technical owner of this multi-quarter effort. The interesting decisions are still open - what we extract first, how we know we're right, what a mature extraction pipeline looks like at our scale. There's no existing approach to inherit or defend.

The work draws on two toolkits:

• 70% applied ML on clinical text: entity extraction, classification, sequence labelling, annotation strategy, error analysis, calibration, and evaluation discipline.
• 30% LLM-based: prompt development, structured output, retrieval, and evaluations and observability.

Deciding which approach a given problem calls for is the most interesting part of the job, and that call is yours.

We're looking for a leader in this seat: setting technical direction rather than waiting to be handed a problem. If this grows the way we think it will, leading the team we build around it is on the table.

Qualifications

• Healthcare or life sciences experience with real clinical data (clinical notes, EHR data, claims, registries, or similar).
• 6+ years in applied ML, with models taken from problem statement to production.
• Depth in applied ML on text: information extraction, NER, classification, sequence labelling, weak supervision, and evaluation practices.
• Practical, current experience with LLM-based approaches: prompt development, structured output, retrieval, fine-tuning, evaluations, and observability.
• Strong engineering fundamentals in Python.
• Strong collaboration instincts across the ML boundary.
• A track record of solving problems rather than closing tickets.

Requirements

• Fluency with clinical terminologies and standards: SNOMED CT, ICD-10, LOINC, RxNorm, CPT, FHIR.
• Experience with HIPAA, SOC 2, de-identification methodology, or IRB and regulatory-grade data work.
• Experience as an early or first ML hire.
• Experience building or running human-in-the-loop annotation and QC operations at scale.
• OCR and document-understanding experience on low-quality real-world documents.
• Experience mentoring or leading ML engineers, or interest in growing that way.

Benefits

• Equity in Novellia.
• Medical, dental, and vision coverage.
• 401(k).
• Flexible time off.
• Wellness stipend.
• Up to 12 weeks of parental leave.