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 or Masters 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.
PhD in Computer Science Data Science Statistics or a related field
3 years of relevant industry experience
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 $147400 and $272100 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 Apples 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 Apples Employee Stock Purchase Plan. Youll 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.
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