Senior ML Engineer - Healthcare NLP, Equity & Flexible PTO

Novellia; Northern (KY); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Equity in Novellia

Medical, dental, and vision coverage

401(k)

Flexible time off

Wellness stipend

Up to 12 weeks of parental leave

Job summary

Novellia is hiring the first ML engineer focused on turning unstructured clinical text into structured, usable data for research and regulatory submissions. You’ll own the end-to-end extraction pipeline, from problem framing to deployment, collaborating with Clinical Data Managers and backend engineers.

Ideal candidates have 6+ years of applied ML with production experience in healthcare data, strong Python skills, and a track record of delivering production-ready models.

Qualifications

• 6+ years in applied ML with production-ready models.
• Healthcare or life sciences experience with real clinical data.
• Depth in information extraction, NLP, and evaluation practices.
• Experience with LLM-based prompts, retrieval, and evals.
• Strong Python engineering skills; production-ready code.
• Collaborative, self-directed, and able to navigate ambiguity.

Responsibilities

• Own the full lifecycle of extraction models from framing to deployment.
• Define acceptable accuracy with stakeholders and build evaluation harness.
• Collaborate with Clinical Data Managers on QA/QC and model specs.
• Build NLP pipelines and productionize tools with backend teams.
• Apply rigorous, versioned prompts and track costs and latency.
• Ensure de-identification and PHI handling are part of the model.

Skills

Applied ML

Healthcare data

NLP

LLM-based approaches

Python

Collaboration

Tools

PyTorch/TensorFlow

Python

Job description

Novellia is hiring the first ML engineer focused on turning unstructured clinical text into structured, usable data for research and regulatory submissions. You’ll own the end-to-end extraction pipeline, from problem framing to deployment, collaborating with Clinical Data Managers and backend engineers.

Ideal candidates have 6+ years of applied ML with production experience in healthcare data, strong Python skills, and a track record of delivering production-ready models.