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Apple AIML - Machine Learning Engineer Model Evaluations United States, California, Cupertino 13241568
Today
Apple Intelligence is driven by intentional data design—spanning careful sampling, creation, and curation of high-quality datasets, enriched with precise annotations. Our data powers our ability to evaluate and mitigate safety risks in new generative AI features. This role sits at the intersection of applied data science, empirical analysis, cultural and linguistic expertise, and stakeholder communication. It requires strong scientific judgment, cross-functional collaboration, and the ability to translate evaluation findings into actionable insights.- Develop metrics for evaluation of safety and fairness risks inherent to generative models and Gen-AI features- Design datasets, identify data needs, and work on creative solutions, scaling and expanding data coverage through human and synthetic generation methods- Partner with policy teams to translate regional safety and inclusivity requirements into measurable evaluation criteria- Build expertise in machine translation and data synthesis techniques to generate localized and culturally aligned evaluation datasets at scale- Work with highly-sensitive content with exposure to offensive and controversial content
- MS or PhD in Computer Science, Linguistics, Cognitive Science, HCI, Psychology, Mathematics, Physics, or a similar science or technology field with a strong basis in scientific data collection and analysis + at least 4 years of relevant work experience, or BA/BS with 8+ years of relevant work experience
- Experience collecting and analyzing language data, image data, and/or multi-modal data
- Strong experience designing human annotation projects, writing guidelines, and dealing with highly multi-labeled, nuanced, and often conflicting data
- Proficiency in data science, machine learning, analytics, and programming with Python & Pandas; strong experience with one or more plotting & visualization libraries
- Excellent interpersonal skills, with a proven ability to synthesize complex findings and present evaluation outcomes to senior leadership and executives
- Strong skills for rigorous model quality metrics development; interpretation of experiments and evaluations; and presentation to executives
- Deep cultural awareness and understanding of regional norms, values, and sensitivities, with the ability to translate this knowledge into actionable evaluation strategies
- Experience in localization, internationalization, or building/evaluating machine learning systems for global markets, with a focus on linguistic and cultural adaptation
- Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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