Apple Inc.
AI Evaluation Data Scientist - Health
Apple Inc., Cupertino, California, United States, 95014
Cupertino, California, United States Hardware
Description
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 Minimum Qualifications
Bachelor's 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 Preferred Qualifications
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 At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .
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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 Minimum Qualifications
Bachelor's 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 Preferred Qualifications
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 At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .
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