Senior ML Manager for 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

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.