Apple

About Apple

The personal technology company redefining user experience

🏒 Tech, HardwareπŸ‘₯ 1001+ employeesπŸ“… Founded 1976πŸ“ Cupertino, CA⭐ 4.2
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Key Highlights

  • Market cap of $3 trillion as of 2022
  • Over 1 billion active devices worldwide
  • Comprehensive medical plans including mental healthcare
  • Paid parental leave and gradual return-to-work program

Apple Inc. (NASDAQ: AAPL), headquartered in Cupertino, CA, is the world's most valuable company with a market capitalization of $3 trillion as of 2022. Known for its iconic products such as the iPhone, iPad, and Mac, Apple serves over 1 billion active devices globally. The company has a strong commi...

🎁 Benefits

Apple offers comprehensive medical plans covering physical and mental healthcare, paid parental leave, and a gradual return-to-work program. Employees...

🌟 Culture

Apple's culture emphasizes an obsessive focus on user experience and consumer privacy, setting it apart from competitors. The company promotes inclusi...

Apple

Ml Infrastructure Engineer β€’ Mid-Level

Apple β€’ Seattle

Apply Now β†’

Overview

Apple is seeking an ML Infrastructure Engineer to enable the Research to Production lifecycle of innovative machine learning models. You'll work with technologies like Python and TensorFlow to build critical infrastructure for on-device machine learning. This role requires experience in machine learning and infrastructure development.

Job Description

Who you are

You have a strong background in machine learning and infrastructure development, with experience in building and optimizing machine learning models for embedded devices. You are proficient in Python and have hands-on experience with machine learning frameworks such as TensorFlow. Your understanding of Kubernetes and Docker allows you to manage containerized applications effectively, ensuring smooth deployment and scalability. You are familiar with the latest trends in machine learning architectures and have a keen interest in exploring new technologies that can enhance on-device capabilities. You thrive in collaborative environments, working closely with cross-functional teams including software and hardware engineers to deliver innovative solutions. You are detail-oriented and possess strong analytical skills, enabling you to benchmark, analyze, and debug complex systems efficiently.

Desirable

Experience with additional machine learning tools and libraries is a plus, as is familiarity with optimization techniques for model performance on constrained devices. A background in research or a related field can further enhance your candidacy.

What you'll do

In this role, you will be responsible for enabling the Research to Production lifecycle of machine learning models that enhance user experiences across Apple’s hardware and software platforms. You will work on onboarding the latest machine learning architectures to embedded devices, developing optimization toolkits to tailor these models for specific targets. Your work will involve building machine learning compilers and runtimes to ensure efficient execution of models, as well as creating a robust benchmarking and debugging toolchain to facilitate continuous improvement of model iterations. You will explore new trends in machine learning architectures and integrate them into our on-device stack, contributing to the development of an end-to-end developer experience for ML development. Collaboration with research, software engineering, and hardware engineering teams will be key to your success, as you will help shape the future of on-device machine learning at Apple.

What we offer

Apple provides a dynamic work environment where innovation thrives. You will have the opportunity to work on cutting-edge technologies that impact millions of users worldwide. We offer competitive compensation and benefits, along with a culture that values diversity and inclusion. You will be part of a team that is at the forefront of machine learning, contributing to projects that redefine user experiences. We encourage you to apply even if your experience doesn't match every requirement, as we value curiosity and a growth mindset.

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