ML Engineer / Applied AI (Extraction)

Contractor · Remote in LATAM · Full-time · Long-term

📍 Remote (Latin America based candidates only).

Turn messy healthcare data into trustworthy structured output — and know when not to trust it.

We are building an AI-native patient access platform that automates scheduling, switchboard, refills, and patient communications for health systems running on EHR systems. We're building agentic systems that replicate real clinical and operational workflows at scale, and we're hiring engineers who have done this kind of work before.

You'll build the extraction pipelines that pull clean, structured data out of the messiest inputs in healthcare, and own the judgment of when that extraction can be trusted.

What you'll do

Build production extraction pipelines for messy healthcare inputs, including documents, faxes, records, call transcripts, and EHR exports.
Own confidence calibration and human-in-the-loop routing to balance automation and accuracy.
Design for messy, real-world data and continuously improve extraction quality through evaluation and iteration.

Tech Stack

Language: Python
AI/ML: LLM-based extraction, OCR, Document AI, NER
Evaluation: Confidence calibration, Human-in-the-loop workflows

What you'll need to do with it

Python: Build and maintain production extraction pipelines.
LLM-based Extraction / OCR / Document AI / NER: Develop and optimize document extraction systems serving real production volume.
Confidence Calibration: Design reliable routing logic for automated and human-reviewed outputs.
ML Evaluation: Analyze errors and improve extraction accuracy at scale.

Bonus

Healthcare documents, HL7, or faxes.
High-volume extraction pipelines.
LLM extraction with structured output.

Why Join

Competitive compensation paid in USD.
100% Remote.
Work on production-grade AI products transforming patient access for leading healthcare organizations.
Paid Time Off: 12 PTO days per year.
Local Holidays: All official holidays in your country.
Birthday Off: Take your special day off.
Career Growth: Clear paths for professional development.
Recognition Program: Celebrate achievements and contributions.
Paid Leaves: Fully covered approved leaves.