Jobs
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Healthcare
•401k
•Equity
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Required Skills
Software Engineering
Machine Learning
Leadership
Distributed Systems
At Apple, we believe machine learning should be deeply integrated, thoughtfully engineered, and responsibly deployed at massive scale. Within the Generative AI Frameworks team, we are building the foundational ML platforms and frameworks that enable teams across the organization to create intelligent, privacy-preserving, and high-impact experiences for millions of users worldwide.
We are looking for an Engineering Manager to lead the development of end-to-end machine learning frameworks that power how models are built, trained, evaluated, and deployed across Apple's services. In this role, you will shape the technical foundations that dozens of product and research teams rely on every day, while building and growing a high-performing engineering team that operates at the intersection of infrastructure, applied ML, and developer experience.
This is an opportunity to influence ML at Apple not through a single product, but by defining the platforms and abstractions that scale innovation across an entire organization.
Description:
This role is responsible for leading a team that designs and delivers shared machine learning frameworks used across Apple services to develop, evaluate, and deploy ML models in production. You will partner closely with applied ML teams, infrastructure teams, and product stakeholders to ensure these frameworks are scalable, reliable, and easy to adopt.
You will set technical direction, manage execution, and grow engineers while balancing long-term platform investments with the immediate needs of product teams. Success in this role requires strong systems thinking, deep empathy for ML practitioners, and the ability to translate ambiguous organizational needs into durable technical solutions.
","responsibilities":"Lead and grow an engineering team building core ML frameworks spanning training, evaluation, deployment, and lifecycle management.
Define the technical roadmap for shared ML infrastructure used across SERVICES.
Partner with applied ML, data science, privacy, and product teams to understand requirements and drive adoption.
Drive architectural decisions that prioritize scalability, reliability, privacy, and developer productivity.
Ensure frameworks support best-in-class model evaluation, experimentation, and continuous improvement.
Foster a culture of engineering excellence, operational rigor, and inclusive collaboration.
Preferred Qualifications:
Experience building shared ML platforms or frameworks used by multiple teams or organizations.
Deep understanding of the ML lifecycle, including training pipelines, evaluation methodologies, and deployment patterns.
Experience operating ML systems at scale in production environments.
Familiarity with model evaluation, experimentation frameworks, and metrics-driven development.
Experience balancing platform abstractions with flexibility for diverse use cases.
Strong technical leadership skills, including architecture reviews and long-term roadmap ownership.
Demonstrated ability to hire, develop, and retain high-performing engineers.
Experience working in environments with strong privacy, security, or compliance requirements.
Minimum Qualifications:
Master's degree in Computer Science or a related field, or equivalent practical experience.
5+ years of professional software engineering experience.
2+ years of people management experience leading engineering teams.
Experience building or maintaining production machine learning systems or platforms.
Strong background in distributed systems, data-intensive applications, or ML infrastructure.
Experience partnering cross-functionally with applied ML or data science teams.
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 $198,300 and $342,800, 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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About Apple

Apple
PublicA 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
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