Sr. Research Manager, Evaluation Science
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 productionize 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.
Description
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. Y ou 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. Y ou 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.","responsibilities":"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.
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Build and lead an ML research team advancing evaluation methods at the frontier. Recruit, develop, and retain topresearch 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. Collaborate on the design of evaluation SDKs and APIs with that end user in mind from the start.
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 .
Preferred Qualifications
Ability to bridge ML research and measurement science. This could mean a machine learning background with genuinefamiliarity with validity and evaluation design, or a measurement science background with strong technical depth in MLmethods
Publications or demonstrated expertise specifically in evaluation methodology (papers about how to evaluate, not just papers that use evaluation)
Demonstrated ability to coach researchers toward higher-impact publications: improving framing, identifying contribution clarity issues, and helping position work for acceptance at top-tier venues
Strong opinions about how evaluation methods should be implemented in user-facing tools: what defaults, abstractions, and guardrails make the difference between a generic SDK and a world-class evaluation platform
Experience designing research with self-service adoption as a first-class constraint, where the end goal is not a bespoke system your team operates but a method or tool that others can apply correctly without deep knowledge of the underlying research
Track record of personally recruiting research talent in competitive hiring markets, including sourcing candidates who would not have applied through standard channels
Minimum Qualifications
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 attractand retain strong research talent
Experience publishing research at top-tier AI/ML venues (NeurIPS, ICML, ICLR, ACL, EMNLP)
Experience partnering with applied science and engineering teams to translate research into production systems, tools, or capabilities adopted by others
Technical depth in AI evaluation, with the ability to critically assess and advance methods for measuring AI system behavior, whether through automated judgment, benchmark design, synthetic data, human evaluation, or other approaches
Demonstrated ability to set research strategy, manage a research portfolio with competing priorities, and make
disciplined investment decisions across near-term and long-term work
Excellent communication skills, including the ability to represent research to executive leadership, partner teams, and the external research community","internalDetails":null
Pay & Benefits
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 $216,600 and $325,500, 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 Apple's 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 Apple's Employee Stock Purchase Plan. You'll 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
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Perks and Benefits
Health and Wellness
Parental Benefits
Work Flexibility
Office Life and Perks
Vacation and Time Off
Financial and Retirement
Professional Development
Diversity and Inclusion
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