Job Details

Job Information

AIML Data Operations - Annotations Production Team Manager
AWM-2012-AIML Data Operations - Annotations Production Team Manager
5/9/2026
5/14/2026
Negotiable
Permanent

Other Information

www.apple.com
Austin, TX, 78703, USA
Austin
Texas
United States
78703

Job Description

No Video Available
 

Weekly Hours: 40

Role Number: 200661924-0157

Summary

Behind every groundbreaking AI innovation at Apple is a foundation of high-quality annotated data—and behind that foundation are the vendor partnerships and production operations that make it possible at scale.

We're looking for an Annotations Production Team Manager to lead a group of crowd managers who serve as the critical link between Apple's annotation needs and our external vendor workforce. You will set strategic direction for how your team engages with vendor partners, ensuring the delivery of high-quality annotated data on time and at scale. You will develop your team's capabilities in vendor management, production operations, and quality oversight while establishing the frameworks and processes that enable consistent, scalable execution. Imagine leading the team that keeps Apple's AI data engine running, ensuring our machine learning models are trained with the highest quality data produced by a global workforce operating at peak efficiency.

Description

As a Manager in Annotations Production, you'll lead a team of crowd managers who collaborate with engineering teams and data requestors to deploy scalable data pipelines through our vendor workforce. Your team manages the full production lifecycle—from initial project requirements and vendor onboarding through delivery tracking, quality assurance, and continuous improvement. You will remain hands-on when complex vendor challenges or production escalations require your direct involvement.

You will coach your team in vendor relationship management, helping them balance quality expectations with throughput targets across multiple annotation domains. You will establish operational frameworks—ramp plans, quality monitoring systems, escalation paths, and performance benchmarks—that enable your team to run production consistently and at scale.

Your work will directly contribute to the success of the next generation of Apple products and features.

This role leads a globally distributed team, with direct reports spanning multiple time zones across regions including [AMR / EMIEA / APAC]. You should be flexible in your working hours to accommodate collaboration across these time zones, which may include early morning or evening meetings on a regular basis.

Minimum Qualifications

  • BS degree required

  • 10+ years of experience in program/project management, production operations, or vendor management in data operations or related fields

  • 3+ years of experience managing and developing teams in operational or vendor-facing roles

  • Strong understanding of production operations including capacity planning, quality assurance frameworks, and delivery management

  • Excellent written and verbal communication skills, with the ability to communicate complex concepts to both technical and non-technical audiences

  • Proven ability to manage multiple concurrent programs with competing priorities in a fast-paced environment

  • Self-motivated and proactive leader who thrives in ambiguous environments and is able to establish diligent processes for global teams

  • Demonstrated ability to navigate ambiguity and rapidly shifting priorities, crafting creative, pragmatic near-term vendor support solutions that keep programs on track while maintaining focus on longer-term vendor strategy and scalable operational goals

  • Experience in leading a dispersed global team

Preferred Qualifications

  • Advanced degree in a relevant field preferred

  • Annotation operations, data operations, or crowd-sourcing programs at scale

  • Vendor/supplier management including performance management and relationship development

  • Budget management and financial forecasting for vendor-delivered work

  • Data quality issue tracking and resolution (impact analysis, root cause analysis, data analysis)

  • Background managing geographically distributed teams or vendor workforces

  • Understanding of machine learning concepts, data annotation methodologies, and quality assurance processes

Other Details

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