Senior Applied Scientist - AI Evaluation & Quality Systems

Senior Applied Scientist - AI Evaluation & Quality Systems Seattle, Washington, United States Machine Learning and AI Apple Services Engineering (ASE) powers the AI and LLM features behind experiences that hundreds of millions of users love every day. As these systems increasingly rely on human-in-the-loop evaluation, the quality of our products is directly constrained by the quality of our evaluation systems. We believe that to build exceptional AI, you need exceptional mechanisms to validate the signals used to train and evaluate them. Description The Human‑centered AI, Data Quality Operations team is looking for a Senior Applied Scientist to join our growing team. We are building the systems and methodologies that make AI evaluation trustworthy, and scalable — directly shaping how Apple develops and validates AI across products and services. In this role, you will develop novel, scalable quality control solutions, working closely with cross‑functional teams to ensure the data powering our AI/ML systems meets the highest standards of accuracy, consistency, and relevance. Your work will span two connected problem spaces. The first is the methodology and tooling that generates reliable ground truth and detects quality failures across human annotation and automated evaluation pipelines. The second is the autonomous QA agents that make those methodologies generalizable across teams and use cases. This role demands fluency across research thinking and engineering execution — you will prototype, validate, and ship. A strong point of view on when not to use a model or agent is as valued here as the ability to build one. Responsibilities Design and implement scalable ground truth generation pipelines across varied task types, annotation modalities, and cold start conditions Build and maintain calibration frameworks that keep LLM evaluators anchored to human judgment over time Develop anomaly detection systems that surface evaluator drift, distribution shifts, and coverage gaps across human annotation and automated evaluation pipelines Design, build, and deploy autonomous QA agents targeting specific facets of evaluation quality, architected for generalizability and self‑service adoption across teams Partner closely with cross‑functional teams to ensure evaluation systems meet the highest standards of accuracy, consistency, and relevance Communicate findings and recommendations clearly to both technical and non‑technical stakeholders, including senior leadership Contribute to a culture of technical excellence by sharing knowledge and best practices across the team Minimum Qualifications 5+ years of industry experience in applied science or machine learning with demonstrated impact on shipped systems Strong hands‑on experience with Large Language Models including prompt engineering and applied use cases such as grading, validation, or classification Strong working knowledge of evaluation methodology for generative AI, including LLM‑as‑a‑judge design, meta‑evaluation, and failure mode analysis Familiarity with human‑in‑the‑loop evaluation systems and the operational dynamics that affect data quality at scale Hands‑on experience designing ground truth generation pipelines across varied task types and annotation modalities Proficiency in Python and relevant ML frameworks, with production experience building, deploying, and monitoring LLM‑based pipelines and agents MS or PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience Preferred Qualifications PhD in Computer Science, Machine Learning, Statistics, or a related field Experience designing agent architectures that are configurable and extensible by practitioners who did not build them Hands‑on experience building anomaly detection systems for evaluation quality, including drift detection, distribution analysis, and systematic bias identificationStrong communication skills with the ability to influence technical direction across cross‑functional teams Demonstrated passion for leveraging AI to improve work efficiency and scale At Apple, base pay is one part of our total compensation package and is determined within a range. The base pay range for this role is between $139,500 and $258,100, 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. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Apple accepts applications to this posting on an ongoing basis. #J-18808-Ljbffr