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Senior Machine Learning Engineer

Apple

Senior Machine Learning Engineer

Apple

Cambridge, MA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Health, dental, and vision coverage

Wellness benefits

Remote work flexibility

Top Tier compensation with equity

Parental leave program

Required Skills

Airflow

Python

PyTorch

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Apple

Senior Machine Learning Engineer

3 weeks ago• Cambridge, MA
Viewed on February 1, 2026
Apply on company site

About Us

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

  • Size: 10000+ employees
  • Industry: Technology, Information Technology, Software, Consumer Goods & Services

View Company Profile:

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 Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop 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 optimize Apple-wide systems & infrastructure. As a member of the fast-paced team, you will have the outstanding and great opportunity to work on new projects and craft upcoming products that will delight and encourage millions of Appleʼs customers ever day.

Description:

To be successful, candidates will need a machine learning background, proven software development skills, a love of learning. They will also need to be able to collaborate with multi-functional teams, including researchers, engineers, data scientists/analysts, and product managers, to help develop and implement machine learning algorithms and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment.

Give to the ongoing improvement of our ML infrastructure and tooling.

Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering

Mentor junior MLEs on the team to ensure best practices are followed

Preferred Qualifications:

PhD or Graduate degree with research/work experience using data science techniques (including but not limited to Computer Science, Statistics, Mathematics, etc).

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, Tensor Flow, Keras, and Py Torch a plus

Minimum Qualifications:

Bachelorʼs degree in Computer Science, Statistics, Mathematics with equivalent experience.

5+ years of related experience building high throughput scalable applications or building machine learning models.

Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building distributed systems.

Experience building data processing pipelines and large scale machine learning systems with experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc.

Skilled in communication, problem solving, critical thinking Attention to detail, data accuracy and quality of output.

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 .

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Perks and Benefits

Health and Wellness

Parental Benefits

Work Flexibility

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Financial and Retirement

Professional Development

Diversity and Inclusion

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About Apple

Apple

Apple

Public

A technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.

10,001+

Employees

Cupertino

Headquarters

$3.5T

Valuation

Reviews

4.0

10 reviews

Work Life Balance

4.0

Compensation

4.2

Culture

3.8

Career

3.5

Management

3.2

75%

Recommend to a Friend

Pros

Great coworkers and people

Excellent benefits and perks

Fast-paced and engaging work environment

Cons

High expectations and pressure

Management quality varies

Limited career progression opportunities

Salary Ranges

17,968 data points

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Data Scientist ICT2

0 reports

$121,979

total / year

Base

-

Stock

-

Bonus

-

$103,682

$140,276

Interview Experience

5 interviews

Difficulty

3.4

/ 5

Duration

28-42 weeks

Offer Rate

20%

Experience

Positive 20%

Neutral 40%

Negative 40%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Behavioral Interview

5

Onsite/Virtual Interviews

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit