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求人Apple

Machine Learning Engineer - Strategic Data Solutions

Apple

Machine Learning Engineer - Strategic Data Solutions

Apple

Austin, TX

·

On-site

·

Full-time

·

2d ago

Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team thatʼs constantly learning and having fun while solving tough business problems? Weʼd love to talk to you if you do! Strategic Data Solutions empowers internal partners and optimizes the customer experience by delivering data-driven solutions across Apple - from fraud mitigation and security to supply chain optimization and fulfillment. This role is on our Fulfillment Operations team, where the enormous scale and complexity of Apple's global supply chain present exciting opportunities for applying machine learning and optimization to real-world logistics problems.

As a Machine Learning Engineer on this team, you will work with partners across Apple, using machine learning and optimization techniques to design, build, deploy, and maintain end-to-end solutions that improve operational efficiency and security, with a direct, measurable impact on the company and our customers.

Our commitment to you: We will provide challenging problems that will engage your curiosity. We will provide an organizational culture that values collaboration, problem-solving, and work-life balance. We will provide mentorship to further develop your technical and leadership skills.

Description

Engage with stakeholders to translate ambiguous business problems into technical solutions

Design data-driven solutions, balancing established techniques with custom approaches where they add value

Collaborate with technical partners to implement robust real-time and batch decisioning in

production

Create reporting and monitor decisioning quality to maintain operational and business metric health

Build end-to-end data pipelines and models to automate and improve fulfillment processes.

Productionize and own the stack

Communicate with stakeholders with varying technical backgrounds and business priorities about your work

Share what you're learning about emerging technologies and methods to improve your team's overall technical capabilities

Preferred Qualifications

PhD in a related field (e.g., Computer Science, Statistics, Operations Research, or similar)

Experience with operations research or mathematical optimization techniques (e.g., linear

programming)

Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact

Experience with AI-assisted coding tools

Minimum Qualifications

Graduate degree with research/work experience utilizing data science techniques (including but not limited to Computer Science, Statistics, Political Science, Biology, etc) or Bachelorʼs degree with equivalent experience

At least 3 years of practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions

Practical experience implementing data science applications in Python or a similar programming language

Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses

Ability to use a querying language such as SQL to extract insights from data

Effective communication skills to translate complex concepts and analysis into concise, business- focused solutions

Team-oriented skills and values to facilitate effective collaboration with business and technical partners

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 $139,500 and $210,100, 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

Apple

Public

Apple 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