Applied Healthcare Researchers

Location: Remote

Company

hirify.global builds a secure, efficient, and privacy-centric platform for exchanging AI training data.

What you will do

• Partner directly with AI researchers at frontier labs and startups working on healthcare models.
• Translate model-development goals into concrete data strategies and identify high-value healthcare data.
• Develop and evaluate fine-tuning, LLM-based extraction, classification, and rules-based methods.
• Design feasibility studies, benchmarks, validation analyses, and error-characterization research.
• Evaluate healthcare datasets, variables, labels, cohorts, schemas, completeness, and required transformations.
• Work with Solutions, FDEs, Data Partnerships, Product, Engineering, and Assessments to operationalize reusable research workflows.

Requirements

• Advanced degree in machine learning, computer science, biomedical informatics, epidemiology, statistics, or a related quantitative field; a Master's degree requires 2+ years of industry experience, or equivalent applied experience.
• Hands-on experience building and evaluating ML or LLM-based systems for extraction, classification, or prediction on real-world data.
• Experience with healthcare data such as claims, EMR/EHR, clinical notes, imaging, or registries.
• Strong Python and SQL skills, with the ability to work independently with large datasets.
• Experience designing evaluations for data quality and dataset representativeness.
• Ability to work directly with technical stakeholders and turn ambiguous goals into concrete research plans.

Culture & Benefits

• Lean, fast-moving, high-trust environment focused on velocity and impact.
• Work emphasizes integrity, resourcefulness, kindness, candor, collaboration, and accountability.
• Opportunity to build reusable research and technical collateral instead of one-off solutions.
• Focus on privacy-preserving transformation, data quality, evaluation design, and task-grounded AI training data.