Job 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. 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 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

Requirements

Must-haves

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
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

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learningpythonsqljava

Platform: apple
Effort: medium