Machine Learning Engineer, Apple Services Engineering

What you'll do

• Design, train, and launch recommendation models to improve relevance and business metrics on App Store surfaces.
• Own ranker modules end-to-end, including candidate representation, feature engineering, and model architecture.
• Conduct offline evaluations, A/B experimentation, and production monitoring for recommendation systems.
• Transition state-of-the-art ranking techniques from research prototypes into production environments.
• Productionize new modeling approaches with high reliability and low latency in partnership with infrastructure teams.
• Ship production-quality code while driving engineering best practices and system architecture.
• Develop novel solutions to power personalized experiences across the App Store for billions of users.

What we're looking for

• Bachelor's and Master's in a quantitative field such as Computer Science, Mathematics, Statistics, or Physics.
• PhD in a quantitative field such as Computer Science, Mathematics, Statistics, or Physics (preferred).
• 3+ years of relevant work experience.
• Hands-on experience with production-level recommender systems.
• Deep knowledge of recommendation systems, design patterns, deep-learning architectures, and multi-task modeling.
• Proven track record of shipping recommendation models to production at scale for billions of users.
• Proficiency with the open-source Python ML/AI tech stack including TensorFlow, PyTorch, scikit-learn, numpy, scipy, and pandas.
• Familiarity with big data technologies and distributed computing such as Spark, Hadoop, and Kafka.