In this role you will: - Design and analyze human evaluations of AI systems to create reliable annotation frameworks and ensure validity and reliability of measurements of latent constructs- Develop and refine benchmarks and evaluation protocols using statistical modeling test theory and task design to capture model performance across diverse contexts and user needs- Conduct statistical analysis of evaluation data to extract meaningful insights identify systematic issues and inform improvements to both models and evaluation processes- Analyze model behavior identify weaknesses and drive design decisions with failure analysis. Examples include but not limited to: model experimentation adversarial testing counterfactual analysis creating tools to assess model behavior and user impact- Collaborate with engineers to translate evaluation methods and analysis techniques into scalable adaptable and reliable solutions that can be reused across different features use cases and evaluation workflows- Work cross-functionally to apply methods to real-world applications with designers clinical experts and engineering teams across Hardware and Software- Independently run and analyze experiments for real improvements
Bachelors degree (or equivalent experience) in a empirical field with emphasis on quantitative methodologies of human behavior including HCI Psychometrics Quantitative or Experimental Psychology Educational Measurement Language Assessment or a relevant field
Proficiency in Python and ability to write clean performant code and collaborate using standard software development practices (e.g. Git)
Strong statistical analysis skills and experience in crafting experiments validating data quality and model performance
Experience in building and extending data and inference pipelines to process large scale datasets
MS and a minimum of 3 years of relevant industry experience or PhD in relevant fields
Real-world experience with LLM-based evaluation systems and human annotation and human evaluation methodologies
Experience in rigorous evidence-based approaches to test development e.g. quantitative and qualitative test design reliability and validity analysis
Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products
Strong communication skills and ability to work cross-functionally with technical and non-technical stakeholders
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