Sr. Applied Scientist, AI Evaluation & Quality Systems

Job description

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. Minimum Qualifications: 5+ years of industry experience in applied science or machine learning, with demonstrated experience building or operating production-grade evaluation, annotation, or quality-assurance pipelines. Hands-on experience designing ground truth generation pipelines across varied task types and annotation modalities, including cold-start scenarios with limited existing data. Experience building real-time monitoring or anomaly/drift detection systems for live data or ML pipelines. Working knowledge of evaluation methodology for generative AI — including LLM-as-a-judge design, meta-evaluation, failure mode analysis, and calibration/reference-guided grading techniques Strong software engineering fundamentals and proficiency in Python and relevant ML frameworks, with production experience building, deploying, and monitoring LLM-based pipelines and agents. Demonstrated ability to work directly with downstream users/stakeholders to incorporate feedback into system design, and to communicate findings clearly to both technical and non-technical audiences. 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 in designing systems or tooling that are configurable and extensible by practitioners who did not build them Strong communication skills with the ability to influence technical direction across cross-functional teams Demonstrated passion for leveraging AI to improve work efficiency and scale