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Research Scientist, AI Evaluation Science

Apple· Apple Services Engineering
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Seattle, WA$205.4k - $308.5kFull-timePosted 7mo ago

About the role

Research Scientist role focused on advancing evaluation methodology for LLMs, agentic systems, and human-AI interaction. Emphasis on original research in evaluation science, publication, and productionizing methods into SDKs and APIs across Apple, with collaboration between ML scientists, measurement scientists, and platform engineers.

Responsibilities

  • Advance evaluation methodology through original research in one or more areas: preference learning and reward modeling (RLHF, DPO, reward hacking mitigation); LLM-as-judge calibration, rubric design, and bias detection; intelligent evaluation strategies including active learning for test selection and automated failure discovery; or validity frameworks for evaluators (construct validity, transfer learning).
  • Publish at top-tier venues (NeurIPS, ICML, ICLR, ACL, EMNLP), contributing to evaluation science as a recognized research area and representing Apple in the research community.
  • Translate research into production-ready tools by partnering with platform engineers to productionize methods into evaluation SDKs and APIs used across Apple.
  • Collaborate with measurement scientists to integrate psychometric methods and validity frameworks into evaluation systems, ensuring evaluators measure what they claim to measure.
  • Define the team's research agenda for evaluation science by identifying high-leverage open problems, validating that they address real-world challenges faced by ML engineers across Apple, and designing rigorous experimental programs to solve them.

Qualifications

  • Ph.D. in Computer Science, Machine Learning, or a closely related field, with a research focus in evaluation-adjacent areas (preference learning, RLHF, human feedback, calibration, automated assessment)
  • Strong publication record at top-tier conferences (NeurIPS, ICML, ICLR, ACL, EMNLP), including first-author publications demonstrating independent research contributions
  • Deep technical expertise in at least one evaluation-adjacent ML area, with strong mathematical foundations: preference learning and reward modeling (RLHF, DPO, reward hacking, specification gaming); OR calibration theory, proper scoring rules, and statistical reliability; OR human-AI interaction methodology (active learning, annotation quality, preference elicitation)
  • Demonstrated ability to implement complex methods from recent papers and run large-scale experiments
  • Track record of translating research into practical systems—prototypes, tools, or methods adopted by others
  • Excellent written and verbal communication skills, including the ability to write clear research papers and explain complex concepts to diverse audiences

Skills

Required:Publication and research communicationML frameworksEvaluation methodologyPreference learning and reward modeling
Nice to have:Calibration theoryActive learning / test selectionCross-disciplinary collaboration

Benefits

  • Comprehensive medical and dental coverage
  • Retirement benefits
  • Discounted products and free services
  • Educational expense reimbursement (tuition)
  • Possibility of discretionary bonuses or commissions
  • Relocation assistance
  • Apple discretionary employee stock programs including RSUs and Employee Stock Purchase Plan (ESPP)
Last updated Aug 21, 2026. Interested? Apply on the company site.

About Apple

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