AI Evaluation Engineer - Health

2 Minutes ago • All levels • Research Development • $147,400 PA - $272,100 PA

Job Summary

Job Description

The Health Sensing team builds outstanding technologies to support our users in living their healthiest, happiest lives by providing them with objective, accurate, and timely information about their health and well-being. As part of the larger Sensor SW & Prototyping team, we take a multimodal approach using a variety of data types across HW platforms, such as camera, PPG, and natural languages, to build products to support our users in living their healthiest, the happiest lives. In this role, you will be at the forefront of developing and validating evaluation methodologies for Generative AI systems in health and wellbeing applications. You will design comprehensive human annotation frameworks, build automated evaluation tools, and conduct rigorous statistical analyses to ensure the reliability of both human and AI-based assessment systems. Your work will directly impact the quality and trustworthiness of AI features by creating scalable evaluation pipelines that combine human insight with automated validation.
Must have:
  • Design and implement evaluation frameworks for measuring model performance, including human annotation protocols, quality control mechanisms, statistical reliability analysis, and LLM-based autograders to scale evaluation
  • Apply statistical methods to extract meaningful signals from human-annotated datasets, derive actionable insights, and implement improvements to models and evaluation methodologies
  • Analyze model behavior, identify weaknesses, and drive design decisions with failure analysis
  • Work across the entire ML development cycle, such as developing and managing data from various endpoints, managing ML training jobs with large datasets, and building efficient and scalable model evaluation pipelines
  • Collaborate with engineers to build reliable end-to-end pipelines for long-term projects
  • Work cross-functionally to apply algorithms to real-world applications with designers, clinical experts, and engineering teams across Hardware and Software
  • Independently run and analyze ML experiments for real improvements
Good to have:
  • MS and a minimum of 3 years of relevant industry experience or PhD in relevant fields
  • Experience with LLM-based evaluation systems and synthetic data generation techniques, and evaluating and improving such systems
  • 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
Perks:
  • Comprehensive medical and dental coverage
  • Retirement benefits
  • A range of discounted products and free services
  • Reimbursement for certain educational expenses (including tuition) for formal education related to advancing your career at Apple
  • Discretionary bonuses or commission payments
  • Relocation
  • Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
  • Eligible for discretionary restricted stock unit awards
  • Can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan

Job Details

The Health Sensing team builds outstanding technologies to support our users in living their healthiest, happiest lives by providing them with objective, accurate, and timely information about their health and well-being. As part of the larger Sensor SW & Prototyping team, we take a multimodal approach using a variety of data types across HW platforms, such as camera, PPG, and natural languages, to build products to support our users in living their healthiest, the happiest lives. In this role, you will be at the forefront of developing and validating evaluation methodologies for Generative AI systems in health and wellbeing applications. You will design comprehensive human annotation frameworks, build automated evaluation tools, and conduct rigorous statistical analyses to ensure the reliability of both human and AI-based assessment systems. Your work will directly impact the quality and trustworthiness of AI features by creating scalable evaluation pipelines that combine human insight with automated validation.

In this role you will:

  • Design and implement evaluation frameworks for measuring model performance, including human annotation protocols, quality control mechanisms, statistical reliability analysis, and LLM-based autograders to scale evaluation
  • Apply statistical methods to extract meaningful signals from human-annotated datasets, derive actionable insights, and implement improvements to models and evaluation methodologies
  • Analyze model behavior, identify weaknesses, and drive design decisions with failure analysis. Examples include, but not limited to: model experimentation, adversarial testing, creating insight/interpretability tools to understand and predict failure modes.
  • Work across the entire ML development cycle, such as developing and managing data from various endpoints, managing ML training jobs with large datasets, and building efficient and scalable model evaluation pipelines
  • Collaborate with engineers to build reliable end-to-end pipelines for long-term projects
  • Work cross-functionally to apply algorithms to real-world applications with designers, clinical experts, and engineering teams across Hardware and Software
  • Independently run and analyze ML experiments for real improvements
  • Bachelors in Computer Science, Data Science, Statistics, or a related field; or equivalent experience
  • Proficiency in Python and ability to write clean, performant code and collaborate using standard software development practices
  • Experience in building data and inference pipelines to process large scale datasets
  • Strong statistical analysis skills and experience validating data quality and model performance
  • Experience with applied LLM development, prompt engineering, chain of thought, etc.
  • MS and a minimum of 3 years of relevant industry experience or PhD in relevant fields
  • Experience with LLM-based evaluation systems and synthetic data generation techniques, and evaluating and improving such systems
  • 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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