Senior Machine Learning Engineer - Ads Relevance & Quality
Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Oct 19, 2026. Apple scores A on the Alion truth index.
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