Machine Learning Engineer

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn't have imagined, and now, can't imagine living without. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do.

Description

APPLE INC has the following available in Cupertino, California and various unanticipated locations throughout the USA. Responsible for low-level algorithmic design and high-level user interface solutions in order to deliver production-quality software for integration into current and future Apple products [iPhone, iPad, Apple Watch, and Mac]. Collaborate with a highly cross-functional software engineering organization on desktop, mobile, and embedded platforms to combine state-of-the-art machine learning techniques with next-generation hardware and software solutions. Modify and improve existing software, design and develop low-level automated recognition systems, and implementation of statistical pattern recognition techniques to deliver new software experiences and improve upon existing ones. Design low-level algorithms and develop machine learning models to enable intelligent user experiences built on machine learning foundations. Handle back-end machine learning software development, data processing, and management of large datasets to enable training and evaluation of new and existing machine learning models. Handle Front-end machine learning software development and optimization of product-facing deliverables to enable powerful machine learning models to run efficiently on embedded devices. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $175,800 - $264,200/yr and your base pay will depend on your skills, qualifications, experience, and location. PAY & BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits: https://www.apple.com/careers/us/benefits.html. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

• Master's degree or foreign equivalent in Information Technology, Computer Science, Machine Learning or related field.
• Education and/or experience must include the following skills:
• Machine Learning research and development, including identifying deep learning model architectures and approaches in computer vision, natural language processing, and signal processing.
• Managing, maintaining, and leveraging large-scale data resources for use of available data in machine learning training and evaluation.
• Using programming language C or C++ for machine learning model deployment and development of on-device user features.
• Developing scalable machine learning training pipeline to build and train machine learning models on distributed clusters.
• Knowledge of machine learning frameworks: PyTorch or Tensorflow
• User interface software development and integration to build internal development tool and interfaces for user-facing features
• Using object-oriented programming paradigm in shipping production code; and, internal tools and infrastructure to enable the creation of productive and modular large project code bases.

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