Machine Learning Engineer

Apple Inc.
Cupertino, United States
26 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source

Tech stack

Embedded Operating Systems Machine Learning Software Engineering Information Technology

Job description

You will work closely with talented Software and ML engineers on our team, and across Apple to train, deploy, and evaluate machine learned models that power new experiences across iOS and all Apple platforms. As we build the future of iOS, you will be responsible for driving the development of the models and infrastructure that power intelligent system experiences. You will be responsible for providing technical leadership across a wide variety of products and features, proposing and executing innovative solutions, and improving our model training and evaluation pipelines in service of quality and future feature development. You will be a core participant in developing new models and architectures that result in high quality features while adhering to device power and performance constraints. We are passionate about user experience and privacy. Our mission is to craft user experiences which leverage the power of machine learning and on-device intelligence to preserve our customers privacy. Come help build state-of-the art intelligence impacting over a billion users.

Requirements

7-10 years of experience:

Shipping and evaluating at scale

Training and deploying machine learned models

Building great user experiences

Working on embedded operating systems

Preferred Qualifications

BS, M.S. or PhD in Software Engineering, Computer Science, Machine Learning, or related field

About the company

Our team is looking for you to help make iOS more intelligent, proactive and personal. Our team is part of the core iOS experience, using privacy preserving on-device intelligence to drive new experiences that touch the lives of millions of Apple customers every day. We are responsible for personalizing core system experiences, such as helping you manage and summarize notifications, get the most relevant widgets in smart stacks, as well as predicting your next Focus. In our team you will bring expertise in machine learning and software engineering to train and deploy models that surprise and delight our customers every day.

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