Sr Software Engineer - Applied Intelligence

Apple Apple · Big Tech · Santa Clara, CA +1 · Software and Services

This role focuses on building native applications and systems for iOS and macOS that integrate machine learning and AI technologies into production experiences. The engineer will collaborate with ML engineers and other teams across Apple to deliver intelligent features for Siri, search, and new product surfaces, with a strong emphasis on the Apple ecosystem's security and privacy.

What you'd actually do

  1. Build native applications and systems that use the full power of iOS and macOS to deliver Apple's knowledge and information experiences
  2. Prototype frameworks and UI to rapidly try out new concepts across search and new product surfaces
  3. Collaborate cross functionally with teams across Apple (iCloud, search, and others) to integrate capabilities end to end
  4. Work alongside ML engineers to bring intelligent features into shipping products
  5. Stay connected with the rapidly changing AI landscape and bring relevant ideas back to the team

Skills

Required

  • 5+ years of experience building software solutions (frameworks, UI, services) for iOS or macOS
  • Track record of working cross functionally with engineers, designers, and ML engineers to ship products
  • Demonstrated ability to work across the full stack (UI, application logic, networking/services)
  • BS or MS in Computer Science, Software Engineering, or equivalent practical experience

Nice to have

  • Strong product focus and ability to advocate for the end user experience
  • Deep understanding of and strong opinions on software quality
  • Comfortable taking ownership and driving quality end to end
  • Experience building software that makes full use of platform capabilities
  • Familiarity with search technologies, information retrieval, or knowledge systems
  • Familiarity with ML concepts or experience integrating ML models into applications

What the JD emphasized

  • critical
  • strong technical opinions
  • bias toward experimentation
  • focus to deliver on time

Other signals

  • integrating machine learning and AI technologies into production experiences
  • collaborate closely with ML engineers
  • bring intelligent features into shipping products