Apple's Commerce & Growth Intelligence team is looking to solve business problems related to the full user lifecycle, including account creation, marketing, personalized offers, subscription ranking, churn prediction, and lifetime value optimization. The ML Applied Research team specifically aims to build and deploy end-to-end machine learning solutions to drive key business outcomes in acquisition, engagement, and retention.
Requirements
- Advanced expertise in machine learning, deep learning, and data mining techniques.
- Proficiency in Python and/or Scala for building, training, and deploying machine learning models for complex, high-dimensional systems.
- Experience with large-scale distributed data processing frameworks such as Spark or Hadoop.
- Strong programming skills and experience with production-level algorithm development.
- Familiarity with reinforcement learning and advanced optimization techniques.
- Experience with personalization systems, recommendation engines, or ranking algorithms.
- Strong understanding of state-of-the-art LLMs and deployment for real-world applications.
Responsibilities
- Design and implement advanced machine learning models to optimize user experiences across Apple’s ecosystem, including App Store, Subscription services, and marketing campaigns.
- Collaborate with cross-functional teams to translate business objectives into technical solutions.
- Lead research and development initiatives, including LLM fine-tuning and the exploration of emerging AI technologies.
- Analyze large-scale datasets to uncover actionable insights, improve model performance, and drive business impact.
- Develop and evaluate prototypes, proof-of-concepts, and production-ready solutions.
- Communicate findings and recommendations effectively to technical and non-technical audiences, including leadership and business partners.
- Contribute to the team’s research goals by authoring publications and filing patents in alignment with Apple’s innovation standards.
Other
- Ph.D. in Machine Learning, Computer Science, Mathematics, Statistics, or a related field, or equivalent work experience.
- Exceptional communication skills, with the ability to present technical concepts and results to diverse audiences.
- Highly self-motivated and results-driven, with a proven ability to thrive in fast-paced, dynamic environments.
- Mentor junior researchers and foster a culture of collaboration, innovation, and excellence within the team.
- Knowledge of marketing analytics, user segmentation, and customer lifetime value modeling.
