AIML Manager, Applied AI Science GenAI Model Autograding, Evaluation

Do you get excited by building and leading a team that redefines how AI products are evaluated Our Evaluation organization is responsible for providing principled assessments across a diverse range of Apple features from Search and Siri to the latest Apple Intelligence capabilities. Within this critical function our team specializes in leveraging advanced AI/ML techniques to enhance both the quality and efficiency of these comprehensive are seeking an experienced and hands-on Manager to lead a team of Applied AI Scientists developing cutting-edge AI/ML models for the automatic grading and quality assessment of our internal GenAI products. You will set the technical direction for autograding at Apple grow the scientists who build it and partner across the company to make trustworthy automated evaluation a foundation that every AI product team can rely on.n

In this pivotal role you will build and lead the team that designs state-of-the-art autograder systems evaluating AI product quality at * Lead and grow a high-performing team of applied AI scientists and machine learning engineers including hiring talent development performance management and building a strong technical leadership layer.n* Set the technical vision and roadmap for autograder development evaluation methodology and toolings. n* Deliver reliable scalable LLM/VLM-based evaluation systems that can be trusted for product-quality decisions.n* Navigate complex technical and organizational challenges resolve cross-functional dependencies and sustain alignment across organizations.n* Identify opportunities to standardize and automate the end-to-end evaluation workflow enabling the team to scale beyond bespoke autograder

MS/PhD degree in Computer Science Machine Learning AI or a related field.n1 years of industry experience building LLM/VLM-based evaluators autograders or automated evaluation systems.n5 years of hands-on experience in machine learning model alignment or benchmark record of managing teams of 3 machine learning engineers and/or AI understanding of GenAI models and their evaluation methodologies including rubric design evaluation set development validation calibration and human-model alignment.

* Strong technical judgment and a track record of leading complex ambiguous AI/ML projects from definition through translating emerging GenAI techniques and research into reliable production-ready scaling AI/ML solutions into reusable platforms frameworks or standardized track record of developing senior machine learning engineers and/or technical ability to align diverse stakeholders around strategy navigate complex situations and drive effective outcomes across organizations.