Sr. Machine Learning Manager, AI, Search & Knowledge Platforms

Apple Inc.; California (MO); On-site; USD 238,000 - 402,000; Full time

Job summary

Apple seeks a Sr. Machine Learning Manager for the Search & Knowledge Platforms group in Cupertino, CA. You will lead backend and ML engineers, set the roadmap for massive indexing/serving systems, and drive initiatives with a focus on scale, reliability, latency, and cost efficiency.

You will guide architecture decisions, develop your team, and partner with quality, infra, and product teams to prioritize impactful work across billions of documents and real-time pipelines.

Qualifications

• Deep expertise in distributed indexing systems and large-scale document processing
• Strong coding skills and solid knowledge of algorithms and data structures
• 10+ years of experience leading and driving large-scale search infrastructure projects, including managing managers
• Experience scaling engineering teams across multiple sites/geographies
• Ability to drive architecture, execution and cross-functional alignment across complex programs spanning multiple teams
• BS, MS, or Ph.D. in Computer Science or related field

Responsibilities

• Lead and mentor a team of backend infrastructure and ML engineers
• Own the technical roadmap for large-scale indexing and serving systems
• Drive execution to meet scale, reliability, latency, and cost targets
• Collaborate with quality, infra, and product teams to prioritize build work
• Oversee work spanning hundreds of billions of documents, petabytes of data, and real-time evaluation pipelines

Skills

Web-scale indexing

Algorithms & data structures

Engineering leadership

Hiring & performance management

Cross-site / cross-geo coordination

Education

BS/MS/PhD in Computer Science or related field

Job description

Sr. Machine Learning Manager, AI, Search & Knowledge Platforms

Cupertino, California, United States Software and Services

Do you want to make Apple products more intelligent for our users? The Search & Recommendation Platforms team is building groundbreaking core infrastructure technology for an AI powered, large scale, highly performant agentic search serving stack. This platform powers search and recommendation experiences across Siri, Safari, Spotlight, App Store, Apple Music, and other Apple products. We are looking for a seasoned Engineering Manager who will build and lead a team of backend infrastructure and ML engineers, own the technical roadmap for large scale indexing and serving systems, and drive execution against aggressive scale, reliability, latency, and cost targets.

Description

We design and build the core infrastructure that indexes and serves billions of documents to find and return the best content to users at query time, with high throughput and low latency. This infrastructure underpins LLM powered and agentic search, spanning indexing, semantic and multimodal retrieval, query understanding, model inference, and agentic orchestration. This role's focus is indexing and serving specifically. As the manager of this team, you will set technical direction, grow and develop your team, and partner across quality, infra, and product teams to prioritize what gets built. You will have the opportunity to lead work spanning hundreds of billions of documents, petabytes of data, and real time evaluation pipelines.

Minimum Qualifications

• Deep expertise in web scale indexing systems, including distributed document processing, storage, and retrieval
• Strong coding skills and background in algorithms and data structures
• 10+ years of experience leading and driving complex, large scale search infrastructure projects Experience managing managers and engineering teams, including hiring, growth, and performance management
• Track record scaling engineering teams across multiple sites/geographies
• Strong technical judgment and ability to drive architecture, execution, and cross functional alignment across complex programs spanning multiple teams
• BS, MS, or Ph.D. in Computer Science or related field

Preferred Qualifications

• Experience designing evaluation infrastructure for large scale indexing and retrieval systems
• Experience with RAG and agentic search scenarios
• Track record of driving developer velocity and quality improvements across large engineering organizations
• Familiarity with LLM model inference, and search quality metrics

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 $237,600 and $401,700, 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.

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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