Engineering Manager, Machine Learning Platform Technologies

Seattle Until 9/21/2026 8+ years exp First posted July 23, 2026 Last posted July 23, 2026
Job description

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. At Apple, the information powering Siri, Spotlight, Apple Maps, and Apple's foundation models doesn't appear by magic, it is harvested continuously from the live web by one of the most demanding distributed crawl platforms in the industry. As Engineering Manager for the Crawl Infrastructure team, you will lead the people and systems responsible for operating a web crawl at petabyte scale and billions of operations per day, feeding the intelligence layer behind Apple's most-used products and the foundation models at the core of Apple Intelligence. This role is for a manager who is technically deep, operationally rigorous, and energized by the challenge of scaling complex distributed systems while growing the engineers around them. You will partner closely with teams across Apple to align infrastructure investment with Apple's most strategic AI and search initiatives.

Description

Apple's web crawl infrastructure is a mission-critical distributed platform that continuously fetches, renders, and extracts structured knowledge from billions of web pages directly powering Siri, Apple Intelligence, Spotlight & Safari. As Engineering Manager for this team, you will lead a group of high performing distributed systems engineers building and operating one of Apple's most complex and consequential data collection platforms.
This is a role for a technically deep manager who can hold the architectural vision for a multi-service pipeline, grow a high-performing team, and partner with downstream product and ML teams to translate real-world knowledge requirements into engineering reality. You will be responsible for building technical roadmap balancing reliability improvements, feature velocity, and platform scalability.
You should be equally comfortable in a production incident war room, stakeholder communication meeting, and a system design review.

Minimum Qualifications

8+ years of software engineering experience, with 3+ years of engineering management experience leading distributed systems engineers in a production environment. Track record of managing senior engineers, setting technical direction, running design reviews, and raising the bar on engineering quality.
Ability to drive large, multi-quarter projects end-to-end, scoping, sequencing, staffing, and delivering against a roadmap.
Experience designing and operating large scale distributed systems, you have personally designed, built, and operated large-scale distributed systems.
Experience with cloud infrastructure at scale, AWS or equivalent, Kubernetes, IaC tooling.
Familiarity with data pipeline infrastructure, streaming (Flink), batch (Spark), and columnar storage (Iceberg or equivalent).
Strong programming background in one of the programming languages, preferred in Rust, Scala, or Go.
BS or MS in Computer Science or equivalent experience.

Preferred Qualifications

Prior experience with web crawl systems is a plus (URL frontier management, politeness, rate limiting, crawl scheduling ).

About this role

Summary

Lead distributed systems engineers to operate and scale Apple's web crawl infrastructure.

Job title

Engineering Manager, Machine Learning Platform Technologies

Experience level

8+ years

Minimum experience

8+ years exp

Industry

technology

Location requirements

Located in Seattle, remote not specified.

Salary

Not specified

Management role

Yes

Skills & keywords

Required skills

software engineeringdistributed systemscloud infrastructureKubernetesRustScalaGo

Preferred skills

web crawl systemsURL frontier managementcrawl schedulingstreamingbatch processing

Specializations

distributed systemsweb crawlingcloud infrastructuredata pipelinesdistributed storage
Locations

Structured locations inferred from the posting.

Seattle, WA, USA

Work arrangement unknown City