AIML - Sr Manager, Evaluation - Data Science & Insights

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. Apple's AIML Evaluation team is looking for a seasoned, technical leader to lead a team within our Data Science and Insights organization. The organization leads Evaluation for Apple Intelligence, Siri AI and a large portfolio of other billion+ user facing features in SWE. Successful candidates will have strong experience in traditional human evaluation methodology, in addition to hands-on experience building and deploying LLM-based autograders and rubrics, and using these tools to proactively drive improvements in models and agentic features. Description As a Senior Manager on the Data Science and Insights team, you'll lead a team of data scientists focused on a core pillar of evaluation, in close collaboration with teams across the company. Your experience will enable you to thoughtfully balance the various tradeoffs involved in creating successful features that meet Apple's high customer expectations for both quality and privacy. Minimum Qualifications 6+ years of experience in data science and machine learning evaluation, including 3+ years leading technical teams Advanced degree in a quantitative field such as Statistics, Computer Science, Machine Learning, or similar Demonstrated track record of running teams of 7+ data scientists and/or machine learning engineers Strong experience in human evaluation methodology for consumer-facing products at scale Hands-on experience building and deploying LLM-based autograders and rubrics, and using them to drive proactive improvements in models and agentic features Strong written and verbal communication skills, able to communicate effectively with engineers and senior leaders Preferred Qualifications Experience evaluating large consumer AI products such as conversational assistants, search systems, or agentic features Experience with logging infrastructure and instrumentation for AI product quality measurement Track record of growing senior individual contributors and leads from within your team and, where needed, recruiting data science and machine learning talent in competitive hiring markets Familiarity with evaluation frameworks for agentic systems and tool-use #J-18808-Ljbffr Socket.dev