Role overview
Support Product Marketing, Investor Relations, and the Executive Team with predictive analytics for customer product and services engagement. Understand product requirements then translate them into modeling tasks and engineering tasks
Develop scalable ML algorithms and models to understand customer behavior and provide leadership with actionable insights and recommendations
Design and implement end-to-end machine learning pipelines-from feature engineering to model serving- using best in class MLOps frameworks
Develop and optimize deep learning and traditional ML solutions on high-volume datasets using GPU clusters or distributed CPU environments.
Experiment with cutting-edge algorithms, providing advanced insights into customer behavior and engagement.
Manage ML projects through all phases, including data quality, algorithm/feature development, predictive modeling, visualization, and deployment and maintenance.
Tackle difficult, non-routine analysis/prediction problems, applying advanced ML methods as needed.
Partner with peers to build and prototype analysis pipelines that provide insights at scale.
Collaborate with data engineers and infrastructure partners to implement robust solutions and operationalize models. Enhance and evolve solutions to meet changing business needs with agility.
What we're looking for
8+ years of hands-on programming skills for large-scale data processing
Graduate degree required in Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or related field
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .