Data Scientist (AI Quality & Evaluation)

ABOUT THE ROLE

We're looking for a Data Scientist to own the quality, reliability, and trustworthiness of our clinical AI outputs. You'll build the systems that ensure our AI "knows what it doesn't know" — developing evaluation frameworks, calibrated confidence scoring, and automated quality assurance that physicians can actually trust.

WHAT YOU'LL DO

- Design and implement automated evaluation pipelines that assess AI output quality, accuracy, and safety at scale

- Develop uncertainty quantification systems where confidence scores meaningfully correlate with accuracy

- Build comprehensive evaluation frameworks combining automated assessment with clinician-validated test cases

- Implement feedback loops that continuously improve model outputs based on validation signals

- Establish scalable quality gates that catch errors before they reach end users

- Contribute to model alignment and fine-tuning efforts

QUALIFICATIONS

REQUIRED

- Strong foundation in deep learning frameworks (PyTorch) and LLM architectures

- Experience with model evaluation, benchmarking, and quality metrics

- Proficiency in Python and modern ML development tools

- Strong statistical foundations

- Ability to read, implement, and extend research papers

- Excellent communication skills

PREFERRED

- Master's degree in Computer Science, Machine Learning, Statistics, or related quantitative field (PhD preferred)

- Publications in top ML/AI venues (NeurIPS, ICML, ICLR, ACL)

- Experience with RLHF, DPO, or preference optimization techniques

- Background in healthcare AI or regulated industries

- Experience building evaluation systems for production LLM applications