Sr. Machine Learning Scientist, Apple Retail Data Sciences

Santa Clara Valley (Cupertino), California, United States
Operations and Supply Chain


Weekly Hours: 40
Role Number:200115792
The people here at Apple don’t just build products — we craft the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that supports the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found it. We are seeking a Senior Machine Learning Scientist to lead our Apple Retail Machine Learning team. You will partner with product managers, engineers and scientists, solving product related problems, conducting experiments, improving the customer experience and driving superlative value through the use of Machine Learning and AI. You will be responsible for: - Collecting, preparing and modeling massive data sets. - Designing machine/deep/reinforcement learning models and optimizing/customizing them for new applications. - Developing production-ready software with scalable, fast and efficient algorithms.

Key Qualifications

  • Deep knowledge of machine/deep/reinforcement learning techniques, with demonstrable expertise in sequence and time series prediction algorithms — Markov Chain, LSTM, GSP, etc.
  • Expert in building production recommender systems on large, real world data sets.
  • Solid foundation using machine learning tools and libraries such as Scikit, Turicreate, TensorFlow, MXNet.
  • Excellent Python/R/Spark coding skills — Swift is a plus.
  • Knowledge of testing, version control, and continuous integration.
  • Experience developing low latency, high throughput machine learning inference engines, designing/maintaining backend APIs and web services is a bonus.


To be successful in this position, you should… Be a self-starter, driven, accountable and a highly upbeat teammate. Have strong writing, data visualization and communication skills with the ability to communicate complex quantitative analysis in a clear, detailed, and actionable manner to senior leaders.

Education & Experience

Bachelor's Degree Minimum Masters Degree Preferred

Additional Requirements