Overview

Summary
Posted: Oct 17, 2024

Role Number:200574145

Imagine what you could do here! The people here at Apple don’t just create products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work.

Here on the Apple Store Online team, we are responsible for Apple’s largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things.

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will lead the way on our Online Retail Decision Automation team by researching and developing the next generation of algorithms used to drive the Apple Online experience! The role spans central areas of our Apple Online Store including developing models for product search, recommendation systems (e.g. ranking, page generation), personalization (e.g. evidence, messaging, marketing), Generative AI and optimizing Apple-wide systems & infrastructure. As a member of the fast-paced team, you will have the outstanding and great opportunity to be part of new projects and craft upcoming products that will delight and encourage millions of Appleʼs customers every day.

Description

Description
To be successful, candidates will need a strong machine learning background, proven software development skills, a love of learning, and to collaborate with cross-functional teams, including researchers, engineers, data scientists/analysts, and product managers, to develop and implement machine learning algorithms. Mentor other MLE’s and lead an effort to build scalable end-to-end machine learning solutions for our retail customers.

RESPONSIBILITIES INCLUDE:
– Ability to build performant production applications with high through put.

– Reading academic papers, apply novel ideas to our problem space and present to stakeholders.

– Provide mentorship and guidance to other machine learning engineers and staying up-to-date with the latest advances in machine learning and software engineering.

– Contribute to the ongoing improvement of our ML infrastructure and tooling, ensuring that we stay at the cutting edge of industry practices.

Minimum Qualifications

Minimum Qualifications
• 10+ years of related experience, including 5+ years experience in machine learning.
• Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systems.
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (eg: Spark, SQL, Snowflake/Hadoop, etc).
• Deep understanding of machine learning model lifecycle from prototyping, feature engineering, training, inference, deployment, monitoring and continuous improvements via deep analysis).

Key Qualifications

Key Qualifications

Preferred Qualifications

Preferred Qualifications
• Ph.D. or Masters in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience.
• Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture.
• Skilled in communication, problem solving, critical thinking.
• Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications a plus.
• Experience with Spark, TensorFlow, Keras, and PyTorch a plus.

Education & Experience

Education & Experience

Additional Requirements

Additional Requirements

Pay & Benefits

Pay & Benefits
• 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 $207,800 and $312,200, and your base pay will depend on your skills, qualifications, experience, and location.

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.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

More
• Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

Company:

Apple

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

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About Apple

Apple is a corporation that designs, manufactures, and markets consumer electronics, personal computers, and software.