Senior Applied Scientist, Multilingual AI Evaluation

About the Role

AI systems are only as trustworthy as the methods used to evaluate them. At Apple, where AI powers experiences for billions of people around the world, getting evaluation right is not a support function—it is a foundational science.

We're looking for a senior applied scientist to make the evaluation tooling we build work across every language and culture Apple serves. This is a role for someone who is fluent in both modern AI and the science of language, and who can set direction and drive initiatives independently, not just execute them. You'll do this on a deeply interdisciplinary team working alongside ML researchers, measurement scientists, and platform engineers.

Responsibilities

• Help ensure Apple's AI features work well across languages and cultures
• Make evaluation tooling multilingual from the start so that engineers building AI features can design, test, and ship across the world from day one
• Shape how Apple evaluates AI wherever the hardest questions are
• Bring linguistic judgment to questions about ensuring consistent evaluation of AI features across different grammar, script, or cultural norms at scale
• Work with measurement scientists and ML researchers to turn linguistic insights into validated methodology that holds across dozens of languages
• Design and implement evaluation methods in Python
• Work closely with research and engineering partners while staying focused on the science of getting evaluation right
• Have the opportunity to publish novel work

Minimum Qualifications

• MS in Linguistics, Computational Linguistics, NLP, Computer Science, or a related field — or equivalent research/work experience
• Deep expertise in linguistics, with working fluency in the structure of multiple languages beyond English
• Strong proficiency in Python
• Solid understanding of LLMs and AI evaluation fundamentals, including how language models process and generate across languages
• Demonstrated experience shipping or evaluating features across multiple languages or locales
• Experience designing benchmarks, datasets, or human evaluation protocols, with attention to statistical rigor and reproducibility
• Ability to drive initiatives independently and collaborate across a cross-functional, interdisciplinary team
• Strong written and verbal communication skills

Preferred Qualifications

• PhD in Linguistics, Computational Linguistics, or NLP with a focus on multilingual or cross-lingual modeling
• Publications in NLP, multilingual evaluation, or evaluation methodology
• Hands-on experience with modern ML frameworks (PyTorch, JAX) and with fine-tuning or evaluating LLMs
• Experience with low-resource languages, dialectal variation, or sociolinguistics
• Familiarity with localization/internationalization workflows and quality assessment
• Experience with LLM-as-judge approaches, rubric design, or bias and fairness evaluation across languages
• Fluency or professional proficiency in one or more languages in addition to English