AIML - Manager, Applied AI Science - LLM/VLM-as-judge
Apple · Cupertino ·
- Category
- AI engineering
- Experience
- 1+ years
- Company size
- 1000+
A hands-on engineering manager role at Apple leading applied AI scientists who build LLM/VLM-based autograders that automatically evaluate the quality of internal GenAI products (Siri, Search, Apple Intelligence). The role covers team leadership, setting the technical roadmap for automated evaluation, and delivering scalable, trustworthy evaluation systems.
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 evaluations.
We 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.
In this pivotal role, you will build and lead the team that designs state-of-the-art autograder systems evaluating AI product quality at scale.
Minimum Qualifications
- MS/PhD degree in Computer Science, Machine Learning, AI, or a related field.
- 1+ years of industry experience building LLM/VLM-based evaluators, autograders, or automated evaluation systems.
- 5+ years of hands-on experience in machine learning, model alignment, or benchmark creation.
- Track record of managing teams of 3+ machine learning engineers and/or AI scientists.
- Deep understanding of GenAI models and their evaluation methodologies, including rubric design, evaluation set development, validation, calibration, and human-model alignment.
Preferred Qualifications
- Strong technical judgment and a track record of leading complex, ambiguous AI/ML projects from definition through delivery.
- Experience translating emerging GenAI techniques and research into reliable, production-ready systems.
- Experience scaling AI/ML solutions into reusable platforms, frameworks, or standardized workflows.
- Demonstrated track record of developing senior machine learning engineers and/or technical leads.
- Demonstrated ability to align diverse stakeholders around strategy, navigate complex situations, and drive effective outcomes across organizations.