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Applied AIML Engineering Manager

Apple

Applied AIML Engineering Manager

Apple

Reedley, CA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Flexible PTO policy

Health, dental, and vision coverage

Annual team offsites

Remote work flexibility

Required Skills

Python

TensorFlow

PyTorch

About the Role

Services at Apple help hundreds of millions of customers get the most out of the devices they love through amazing apps, award-winning shows and movies, immersive music in spatial audio, world-class workouts and meditations, super fun games and more! The Services Data Science & Analytics organization is passionate about developing discerning insights and AIML solutions to help continually improve these services and accelerate growth while maintaining a strong dedication to customer privacy.

We are currently seeking an experienced and passionate Applied AIML Engineering Manager to lead a dynamic team, whose goal is to help optimize customer-facing features at scale through use of Generative AI and other privacy-preserving predictive models centered around customer state changes, engagement, and other forms of personalization. As a key member of our diverse organization, you'll have the rare and rewarding opportunity to work with server-side and on-device datasets of unique magnitude, richness, and dedication to privacy that will frequently require innovative approaches. You'll work alongside partners across Business, Marketing, Product, Finance, and Engineering daily to deliver material customer and business value.

As an Applied AIML Engineering Manager, you will have the responsibility of leading a highly talented team of engineers dedicated to pushing the boundaries of how AI and ML can be leveraged to better serve our customers, focusing on Services such as Apple TV, Apple Music, Apple Arcade, Apple One, and the App Store. You will be at the forefront of designing, developing, and deploying cutting-edge AIML solutions, including via Generative AI, that directly impact our products and provide a granular understanding of customer preferences and user value drivers. You will also be instrumental in defining the technical vision, strategy, and execution roadmap for our AIML initiatives, ensuring that we deliver high-quality, scalable, and impactful models that solve complex customer acquisition and engagement challenges. Beyond technical leadership, you will be a key driver in fostering a vibrant culture of AIML innovation, continuous learning, and collaborative problem-solving within your team.

Responsibilities

  • Lead, mentor, and grow a high-performing team of AIML engineers, fostering a culture of innovation and collaboration
  • Drive team goals, priorities, and career development, including recruitment and onboarding
  • Oversee the technical strategy, design, and full AIML lifecycle of scalable, robust models and systems
  • Manage timelines, resources, and deliverables, ensuring projects are completed on time, within scope, and communicated to stakeholder teams
  • Collaborate with product managers, data scientists, and other engineering teams to translate business requirements into technical specifications and deliver impactful, practical solutions, increasing internal adoption of AIML products and democratizing data
  • Stay abreast of the latest advancements in AIML research and technologies, evaluating and integrating new approaches where appropriate
  • Champion best practices in software engineering, MLOps, code quality, testing, documentation, and ensure compliance with data privacy and security

Minimum Qualifications

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, Engineering, or a related technical field
  • 3+ years of experience in a leadership or management role, leading Machine Learning Engineers and Software Engineers
  • 5+ years of experience in a machine learning or software engineering role
  • Familiarity with emerging AIML technologies including Generative AI and AI Agents
  • Proven track record of successfully delivering complex AIML projects from conception to production
  • Deep understanding of machine learning algorithms, deep learning frameworks, and statistical modeling
  • Proficiency in programming languages such as Python, SQL, Java, or C++
  • Experience with cloud platforms, Spark, Docker, and MLOps tools and best practices
  • Strong understanding of data structures, algorithms, and distributed systems
  • Excellent communication, collaboration, and presentation skills with meticulous attention to detail

Preferred Qualifications

  • PhD in related field
  • Hands-on experience leveraging Generative AI to improve customer-facing experiences, preferably for an internet technology company
  • Curious business attitude with an ability to condense complex concepts and models into clear and concise takeaways that drive action

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