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. Our team, part of Apple Services Engineering, is building that scientific foundation: rigorous, scalable evaluation methodology for LLMs, agentic systems, and human-AI interaction.
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.
In this role, you’ll help ensure Apple’s AI features work well across languages and cultures. Your goal is to make our evaluation tooling multilingual from the start so that engineers building AI features can design, test, and ship across the world from day one. It’s a broad applied science role: you’ll shape how Apple evaluates AI wherever the hardest questions are, and you’ll have the opportunity to publish novel work.
The scientific challenge is real. How do we ensure we consistently evaluate AI features across different grammar, script, or cultural norms and how do we do this at scale? You’ll bring linguistic judgment to questions like these and, working with measurement scientists and ML researchers, turn it into validated methodology that holds across dozens of languages.
This is a hands-on role. You’ll design and implement your own methods in Python, working closely with research and engineering partners, while staying focused on the science of getting evaluation right.