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Machine Learning Research Scientist - Personalization Science, Apple Fitness+
Cupertino, CA
·
On-site
·
Full-time
·
1d ago
Wonder how Apple's Media Products show relevant search results and recommendations across App Store, Apple TV, Apple Music, Apple Podcasts, Apple Books, and Apple Fitness+? Join us to conduct research and develop machine learning models that personalize Apple Fitness+ for millions of users worldwide! In this role, you will propose, prototype, and evaluate innovative algorithm solutions and improvements. You will partner to build large-scale personalized recommender systems across Apple's media products and see your work touch the lives of billions of Apple users worldwide.
The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the team that powers recommendations and personalization in the App Store, Apple TV, Apple Music, Apple Podcasts, Apple Books, and Apple Fitness+. We achieve this on a massive scale, meeting Apple's high privacy expectations, and delivering a vast array of fitness and wellness content in over 35 languages to more than 150 countries. Our scientists and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software and services, designers, scientists, and engineers partner to get behind a single unified vision that always includes a deep commitment to strengthening Apple's privacy policy. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
Description
We are looking for a world-class researcher to help us solve challenging problems in personalization science using the latest advances in artificial intelligence and machine learning. With your expertise, we want to develop novel solutions to power personalized experiences in Apple Fitness+ that enrich our customers' lives by helping them achieve their health and wellness goals. You will have the incredible opportunity to see your solutions deployed at Apple's truly incredible global scale.","responsibilities":"Develop and apply state-of-the-art machine learning and artificial intelligence techniques to personalize user experiences within Apple Fitness+.
Conduct human evaluation and rigorous experiments to test and improve your models.
Derive insights from experimentation and convert them into feature improvements.
Ship production quality code to deploy your models at a global scale.
Contribute to the scientific literature through publications and participation in leading academic conferences.
Help chart the future growth of personalization across Apple's services ecosystem.
Preferred Qualifications
PhD in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.
Knowledge of generative artificial intelligence applied to recommendation systems.
Minimum Qualifications
Deep knowledge of machine learning-powered personalization algorithms, design patterns, and tools. In particular, this includes deep learning, reinforcement learning, and unsupervised learning methods.
Practical real-world experience with building scalable recommendation systems.
Proven grasp of the open-source Python ML/AI tech stack, including Tensorflow, Py Torch, scikit-learn, numpy, scipy, and pandas.
Technical competence in production-quality software development.
Familiarity with big data technologies.
Strong written & oral communication skills.
MS in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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 .
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 $181,100 and $318,400, 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.
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Appleについて

Apple
PublicApple Inc. is an American multinational technology company headquartered in Cupertino, California, in Silicon Valley, best known for its consumer electronics, software and online services.
10,001+
従業員数
Cupertino
本社所在地
$3.5T
企業価値
レビュー
3.9
10件のレビュー
ワークライフバランス
2.5
報酬
4.2
企業文化
3.8
キャリア
3.5
経営 陣
3.2
72%
友人に勧める
良い点
Great benefits and compensation
Talented colleagues and supportive teams
Learning opportunities and mentorship
改善点
Work-life balance challenges
High stress and pressure
Fast-paced environment
給与レンジ
11,365件のデータ
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Principal/L7
Senior/L5
Staff/L6
Junior/L3 · Data Scientist ICT2
0件のレポート
$121,979
年収総額
基本給
-
ストック
-
ボーナス
-
$103,682
$140,276
面接体験
3件の面接
難易度
3.3
/ 5
期間
28-42週間
内定率
33%
体験
ポジティブ 33%
普通 0%
ネガティブ 67%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
よくある質問
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
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