At Apple, the business problem is to ensure high-quality, trustworthy ad experiences by building intelligent systems to evaluate ad relevance, detect low-quality or offensive content, and optimize user satisfaction.
Requirements
- 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
Responsibilities
- Design and implement machine learning models to evaluate and improve ad relevance, trust, and quality for user queries
- Build NLP and multi-modal models that detect offensive, unsafe, or policy-violating content at scale
- Develop methods for semantic query understanding, ads understanding, relevance scoring, and keyword-to-ad matching
- Collaborate closely with product and policy teams to translate content integrity standards into measurable ML objectives
- Work with large-scale, privacy-preserving datasets to discover and operationalize new quality signals
- Conduct offline/online experiments to measure impact on user trust and satisfaction across Ads
- Partner cross-functionally with infrastructure, product, and moderation teams to deploy models at production scale
Other
- MS in Computer Science, Machine Learning, NLP, or a related technical field
- Strong problem-solving and communication skills with a focus on translating abstract trust/safety goals into deployable solutions
- 4+ years of experience
- PhD in Computer Science, Machine Learning, NLP, or a related technical field (preferred)
- Ability to work in a team and collaborate with cross-functional teams
