Lead, AIML Data Ops Engineering

Apple Inc.; Cupertino (CA); On-site; USD 206,200 - 356,400; Full time

Benefits offered by this job

Stock programs

Discretionary bonuses

Relocation assistance

Medical and dental coverage

Tuition reimbursement

Job summary

Apple Inc. is seeking a Sr Software Engineering Manager for AIML Data Operations in Cupertino, CA. You will lead a team building software powering machine learning data collection and delivery at Apple scale, spanning Swift apps, cloud services, and large-scale data pipelines.

You will set direction, foster engineering culture, hire and mentor engineers, and collaborate with ML researchers, data scientists, and product teams to deliver scalable solutions with a strong customer focus.

Qualifications

• 5+ years managing software engineering teams, including direct management of 10+ engineers
• 8+ years experience designing and operating production-grade software systems
• Experience leading cross-functional software programs
• Strong communication and ability to present to executives
• Expertise in modern object-oriented languages (Swift, Objective-C, Go, C++, Java)

Responsibilities

• Lead a team of software engineers building internal tools for ML data collection and delivery
• Set technical direction and engineering culture, best practices
• Partner with ML researchers, data scientists, and product teams to deliver scalable software
• Hire, mentor, and grow engineers at multiple levels
• Communicate program status and technical strategy to executives

Skills

Team leadership

Cross-functional collaboration

Swift/Obj-C/Go/C++/Java

Cloud services

Distributed data processing

Education

Bachelor's degree in CS/SE or related field

Job description

Apple Inc. is seeking a Sr Software Engineering Manager for AIML Data Operations in Cupertino, CA. You will lead a team building software powering machine learning data collection and delivery at Apple scale, spanning Swift apps, cloud services, and large-scale data pipelines.

You will set direction, foster engineering culture, hire and mentor engineers, and collaborate with ML researchers, data scientists, and product teams to deliver scalable solutions with a strong customer focus.