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Applied Machine Learning Engineer - Customer Feedback

Apple

Applied Machine Learning Engineer - Customer Feedback

Apple

Cupertino, CA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Top Tier compensation with equity

Annual team offsites

Health, dental, and vision coverage

Parental leave program

Wellness benefits

Learning and development stipend

Required Skills

TensorFlow

Python

PyTorch

About the Role

Join the team responsible for Apple's Feedback and Beta Programs! Our tools and applications collect user feedback on beta software releases, helping to drive the direction and priorities of Apple's engineering teams. To make the best use of feedback we receive from customers and developers, we develop and maintain machine learning systems and automated analysis to cluster, annotate, and escalate the millions of reports we receive yearly.

We are looking for experienced Machine Learning engineers to deploy and tune both traditional ML and generative AI models to enhance our systems' capability. There are tantalizing problems and products possible with our one-of-a-kind dataset, and plenty of opportunity for a passionate engineer.

Description

Our team is seeking adept machine learning engineers who are excited by creating machine-learning-driven user experiences. Work includes implenting high-performance machine learning models and infrastructure in concert with software engineers, designers, and teams of internal users.

You will be responsible for full stack ML development in partnership with others on the team. This includes data generation and curation, creating and influencing ML tooling and infrastructure, driving evaluation efforts, and training or fine-tuning models. You will also be involved in directly integrating ML into internal tools and systems. You will need to rely on your creativity and problem solving to develop scalable, maintainable, and cost-effective solutions.

The team values rapid iteration, based on bringing models into reality so stakeholders can play with cutting edge technology and research. To this end you will be engaged with hardware, software, and design teams across Apple; both representing the technology and implementing it into prototypes.

You will be successful and feel fulfilled in our team if you enjoy tackling challenging problems, have a strong sense of shared ownership, and thrive in a collaborative team setting.

Preferred Qualifications

  • Working knowledge of applied Natural Language Processing
  • Strong hands-on experience in building large scale ML based solutions or in building and scaling distributed systems

Minimum Qualifications

  • Industry experience with applied machine learning
  • Industry experience in software engineering, data engineering, or similar
  • Strong fundamentals in problem solving, algorithm design, and model building
  • Excellent verbal and written communication and presentation skills
  • MS in Computer Science or related experience

Equal Opportunity

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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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