Apple-posted 2 months ago
Cupertino, CA
5,001-10,000 employees
Computer and Electronic Product Manufacturing

At Apple, new ideas have a way of becoming excellent products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! The Product Marketing Customer Analytics team is seeking a Machine Learning Engineer with deep technical experience in predictive analytics and analytic engineering. 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.

  • Support Product Marketing, Investor Relations, and the Executive Team with predictive analytics for customer product and services engagement.
  • Translate product requirements into modeling and engineering tasks.
  • Develop scalable ML algorithms and models to understand customer behavior.
  • Provide leadership with actionable insights and recommendations.
  • Design and implement end-to-end machine learning pipelines using MLOps frameworks.
  • Develop and optimize deep learning and traditional ML solutions on high-volume datasets.
  • Experiment with cutting-edge algorithms to gain insights into customer behavior.
  • Manage ML projects through all phases including data quality and deployment.
  • Tackle difficult, non-routine analysis/prediction problems using advanced ML methods.
  • Partner with peers to build and prototype analysis pipelines.
  • Collaborate with data engineers and infrastructure partners to implement robust solutions.
  • Enhance and evolve solutions to meet changing business needs.
  • 8+ years of proven experience building and scaling predictive models across distributed systems.
  • 8+ years of hands-on programming skills in Python and/or Spark for large-scale data processing.
  • Experience developing machine learning models on structured and unstructured data.
  • Demonstrated success maintaining robust, high-throughput ML pipelines in a production environment.
  • Comfortable with advanced deep learning frameworks such as Tensorflow and PyTorch.
  • Adept at designing and scaling ML platforms including feature stores and automated retraining pipelines.
  • Solid technical database and data modeling knowledge (Oracle, Hadoop, SnowFlake).
  • Experience optimizing SQL queries on large datasets for performance-critical analytics.
  • Ability to work effectively on ambiguous data in a fast-changing environment.
  • Strong communication skills to explain complex technical topics to both technical and non-technical stakeholders.
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