Machine Learning Engineer
About the role
You'll own the ML end-to-end: turning clinical fidelity rubrics into a well-posed extraction and scoring problem, curating ground-truth data with clinical reviewers, building evaluation against expert raters, and fine-tuning open-weight models as our dataset grows.
We want real ML/DL chops: training and fine-tuning, data labeling and quality control, and the ability to translate a clinical question into a computational problem. We care about what you've shipped and how you reason, not years of experience.
About Kuddo
We're building the quality measurement layer for behavioral healthcare: AI that surfaces whether clinicians are delivering evidence-based protocols with fidelity and closes the gap with targeted feedback. We believe AI should make experts better, not replace them.
Contract-first, with full-time conversion after our seed close this summer. Our mission is to give everyone the toolkit for a life well-lived, starting with empowering those on the frontline who share that mission to do their best work.
Responsibilities
- Turn clinical fidelity rubrics into a well-posed extraction and scoring problem
- Curate ground-truth data with clinical reviewers
- Build evaluation pipelines against expert raters
- Fine-tune open-weight models as the dataset grows
Skills
- Training and fine-tuning machine learning/deep learning models
- Data labeling and quality control
- Translating clinical questions into computational problems