SRE Manager, ML Operations

Apple Inc.; New York (NY); On-site; USD 228,100 - 342,800; Full time

Benefits offered by this job

Comprehensive medical and dental coverage

Retirement benefits

Discounted products and free services

Education reimbursement

Job summary

Apple Inc. is seeking a senior engineering leader in New York City to manage and grow the Site Reliability Engineering team focused on ML Operations. This role will involve shaping the future of ML platforms and services while emphasizing operational excellence and innovation.

The ideal candidate will have substantial experience leading engineering teams, deep technical expertise in large-scale systems, and a strong focus on collaboration across various teams to deliver impactful initiatives.

Qualifications

• 10+ years of experience with large-scale distributed systems.
• 5+ years of experience in an engineering leadership role.
• Proven track record of building and leading high-performing teams.

Responsibilities

• Lead and scale SRE teams for ML Platforms.
• Grow and develop engineers through mentorship.
• Define a compelling team vision and drive execution.
• Champion best practices including SLOs/SLAs.
• Partner on architecture decisions and long-term strategy.

Skills

experience with large-scale distributed systems

experience in engineering leadership

problem-solving skills

communication skills

decision-making skills

Education

Bachelor's or Master's in Computer Science or related field

Tools

AWS

GPU-based clusters

Job description

New York City, New York, United States Software and Services

Description

We are looking for a senior engineering leader to manage and grow our Site Reliability Engineering team, with a focus on ML Operations. This team owns the reliability, performance, and scalability of the Ad Serving infrastructure that serves as the critical front door of Apple Ads — operating at one of the largest scales in the industry. This is a high‑impact leadership role where you will shape the future of how we build, run, and evolve our ML Platforms and Services globally. You will bring deep technical expertise while staying anchored to business and product goals, and you will cultivate a team culture defined by operational excellence, innovation, and continuous improvement.

Responsibilities

• Lead and scale SRE teams responsible for the reliability, performance, and availability of ML Platforms and Services
• Grow and develop your engineers through mentorship, clear goal‑setting, and meaningful career development
• Define a compelling team vision and drive execution toward high‑quality, measurable outcomes
• Champion reliability engineering best practices including SLOs/SLAs, error budgets, observability, incident management, and fault analysis
• Foster a culture of engineering excellence – encouraging innovation, knowledge sharing, and continuous improvement
• Partner with staff engineers and technical leadership on architecture decisions, platform strategy, and long‑term roadmap
• Collaborate cross‑functionally with Product, ML Platform, Ads Serving, and Data Science teams to deliver complex, high‑impact initiatives

Minimum Qualifications

• 10+ years of experience with large‑scale distributed systems
• 5+ years of experience in an engineering leadership role, ideally managing SRE or Production Engineering teams
• Proven track record of building and leading high‑performing engineering teams
• Strong grasp of core operating system principles, networking fundamentals, and systems management
• Deep understanding of SRE principles: monitoring, alerting, error budgets, fault analysis, capacity planning, and incident response
• Excellent problem‑solving, communication, and decision‑making skills

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science or a related field
• Experience managing and optimizing GPU‑based clusters in production environments
• Experience building and operating large‑scale ML systems or ML infrastructure at scale
• Hands‑on experience managing cloud infrastructure, particularly AWS
• Familiarity with the digital advertising ecosystem and its technical demands
• Demonstrated ability to influence and partner across Product, Data Science, and Platform Engineering organizations

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 $228,100 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.

Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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