Senior Applied Scientist - AI Evaluation & Quality Systems

Apple • Seattle, WA

1d

About The Position

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.

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.

Requirements

• 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

Nice To Haves

• 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 identification
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees