Senior Machine Learning Engineer - Ads Relevance & Quality

At Apple, we focus deeply on our customers’ experience. Apple Ads brings this

same approach to advertising, helping people find exactly what they’re looking

for and helping advertisers grow their businesses! Our technology powers ads and

sponsorships across Apple Services, including the App Store, Apple News, and MLS

Season Pass. Everything we do is designed for trust, connection, and impact: We

respect user privacy, integrate advertising thoughtfully into the experience,

and deliver value for advertisers of all sizes—from small app developers to big,

global brands. Because when advertising is done right, it benefits everyone!

Apple’s Ads team is seeking a highly skilled and motivated Machine Learning

Engineer to join the Ads Relevance and Quality team. This team is responsible

for ensuring high-quality, trustworthy ad experiences by building intelligent

systems to evaluate ad relevance, detect low-quality or offensive content, and

optimize user satisfaction. You’ll work at the intersection of applied ML, NLP,

and content quality—designing models and systems that understand queries, flag

inappropriate content, and raise the bar for ad relevance and user trust across

billions of queries and impressions.

DESCRIPTION

You’ll play a key role in shaping the future of safe, high-quality advertising

at Apple. Your work will help ensure that ads remain useful, relevant, and

respectful of our users—supporting Apple’s values of privacy, trust, and

transparency. You’ll collaborate with world-class engineers and researchers,

apply cutting-edge ML techniques in real-world systems, and have a direct impact

on the experience of millions of users every day.

MINIMUM QUALIFICATIONS

4+ years of experience applying machine learning at scale in domains such as ad

tech, content moderation, search ranking, or recommendation systems Strong

expertise in natural language processing, including offensive content detection,

semantic matching Experience with Transformer-based architectures (e.g., BERT,

DistilBERT) and training pipelines in TensorFlow or PyTorch Familiarity with

fine-tuning Large Language Models (LLMs) for downstream tasks such as

classification, content moderation, or semantic relevance Familiarity with

quality and fairness evaluation frameworks (precision, recall, coverage, policy

alignment, etc.) Hands-on experience with A/B testing, experimentation

frameworks, and performance debugging in production Proficiency in Python and

SQL Strong problem-solving and communication skills with a focus on translating

abstract trust/safety goals into deployable solutions MS in Computer Science,

Machine Learning, NLP, or a related technical field

PREFERRED QUALIFICATIONS

7+ years of experience applying machine learning at scale in domains such as ad

tech, content moderation, search ranking, or recommendation systems PhD in

Computer Science, Machine Learning, NLP, or a related technical field Additional

experience in Scala or Java