Sr. Research Manager, Evaluation Science

Sr. Research Manager, Evaluation Science

Seattle, Washington, United States Software and Services

AI systems are only as trustworthy as the methods used to evaluate them. At Apple, where AI powers experiences for billions of people, getting evaluation right is not a support function. It is a foundational science. As these systems grow in complexity, the quality of our products is increasingly constrained by the quality of our evaluation methods. Our team is building the scientific foundation and self‑service tools for how AI evaluation is done at scale, spanning LLMs, agentic systems, and human‑AI interaction.

We don’t just publish methods; we product ionize them. We are looking for a Sr. Research Manager to lead an ML research team that advances the state‑of‑the‑art in evaluation methods that can be shipped as production tools for Apple developers and published in top venues.

We are looking for a Sr. Research Manager to lead a ML research team advancing the frontier of evaluation methods. The team works in close collaboration with applied scientists and measurement scientists to build evaluation methodology and systems that are human‑centered, psychometrically rigorous, and technically frontier. You will set the research agenda, direct the team's portfolio across near‑term and long‑term bets, and ensure that novel methods are designed from the outset for productionization into evaluation SDKs and APIs.

The team has active projects across multiple research areas; your most immediate contribution will be bringing strategic focus to this portfolio, leading a research lifecycle that turns your team’s work into high‑impact internal applications, and positioning work for external impact at top‑tier venues. You will have a strong ML background and a track record of leading research teams that publish at venues like NeurIPS, ICML, and ICLR while simultaneously shipping methods into production tools.

What makes this team unusual is its interdisciplinary core. You will lead ML researchers working alongside measurement scientists and applied scientists, bringing together frontier ML research, psychometric rigor, and production engineering. What unites the strongest candidates is depth of thinking about evaluation as a research problem and the conviction that how we measure AI systems is as important as how we build them.

• Set and execute the research strategy, defining a balanced portfolio and making clear investment decisions between near‑term capability work and longer‑term scientific bets.
• Build and lead an ML research team advancing evaluation methods at the frontier. Recruit, develop, and retain top research talent through a compelling research vision, strong mentorship, and a culture that values both publication and the translation of novel methods into working systems.
• Maintain a strong external research presence at top venues while delivering evaluation capabilities that are adopted internally. Design research projects scoped from inception for productionization.
• Partner with platform engineering and applied science partners to translate research into self‑service evaluation infrastructure. The goal is not just a working system but rather an abstraction that an Apple engineer without a research background can apply correctly.
• Identify the evaluation problems most worth solving across Apple and ensure your team's work is designed to address them. The goal is not just research outputs but capabilities that other teams can adopt without needing your team to operate them.
• Create an environment where interdisciplinary researchers can collaborate productively without flattening the distinct expertise each discipline brings.
• Serve as a visible leader in evaluation science, representing the team at conferences, workshops, and in the broader research community.

• Ph.D. in Computer Science, Machine Learning, Statistics, or a closely related field
• 5+ years of experience managing or leading research teams in an industry setting, with demonstrated ability to attract and retain strong research talent
• Experience publishing research at top‑tier AI/ML venues (NeurIPS, ICML,…