SRE Manager, ML Operations

At Apple, we believe technology should enrich people's lives. Our advertising platform is built on that same principle — delivering ads in a way that genuinely benefits customers, advertisers, and creators alike. We help people discover content they love, support the developers and publishers who build it, and do it all with the unwavering commitment to privacy that Apple is known for.

Our technology powers advertising across the App Store, Apple News, Stocks, and Apple TV. From helping developers drive app discovery to enabling brand-safe display advertising alongside trusted journalism, everything we do reflects a simple belief: when advertising is done right, it benefits everyone.

## 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.

## 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