Senior Applied Scientist - Ai Evaluation & Quality Systems
Apple
United States Of America, United States
Not specified; not specified; not specified
Not specified (assumed hybrid based on industry norms).
5+ years industry experience in applied science
Strong hands-on experience with large language models
Proficiency in python and ml frameworks
Apple is seeking a Senior Applied Scientist for its AI Evaluation & Quality Systems team, focusing on developing scalable quality control solutions for AI systems. The ideal candidate will have extensive experience in machine learning, particularly with Large Language Models, and a strong understanding of evaluation methodologies
Job Summary
This role involves developing novel, scalable quality control solutions to validate signals used to train and evaluate AI systems.
The team focuses on building methodologies that generate reliable ground truth and detect quality failures across human annotation and automated evaluation pipelines.
Candidates must demonstrate fluency across research thinking and engineering execution to prototype, validate, and ship autonomous QA agents.
Matching Summary
Match Score: 85
Apple is seeking a Senior Applied Scientist for its AI Evaluation & Quality Systems team, focusing on developing scalable quality control solutions for AI systems. The ideal candidate will have extensive experience in machine learning, particularly with Large Language Models, and a strong understanding of evaluation methodologies.
Salary
Not specified; Not specified; Not specified
Skills & Requirements
Must-have
5+ years industry experience in applied science
Strong hands-on experience with Large Language Models
Proficiency in Python and ML frameworks
Experience designing ground truth generation pipelines
Knowledge of LLM-as-a-judge design and meta-evaluation
Nice-to-have
PhD in Computer Science or related field
Experience building configurable agent architectures
Passion for leveraging AI to improve work efficiency
Ability to influence technical direction across teams
Key Requirements
MS or PhD in Computer Science, Machine Learning, Statistics, or related quantitative field
5+ years of industry experience in applied science or machine learning
Production experience building, deploying, and monitoring LLM-based pipelines