Senior Manager - AI Data Operations

Apple Apple · Big Tech · Austin, TX · Software and Services

The Senior Manager of AI Data Operations will lead an organization of internal domain experts to build scalable annotation programs that balance accuracy and speed while maintaining quality standards. This role partners with Engineering, Data Science, and Programs to translate evolving system requirements into robust audit pipelines, tooling strategies, and measurable performance lift. Responsibilities include owning end-to-end data annotation and system audit operations, designing quality frameworks, operationalizing auditing for training, evaluation, and red-teaming, driving tooling evolution and automation strategy, and developing data augmentation strategies.

What you'd actually do

  1. Own end-to-end data annotation and system audit operations, including the strategy, workflow designs, execution, and performance optimization.
  2. Design quality frameworks including gold sets, inter-rater reliability systems, audits, and error taxonomies.
  3. Operationalize auditing for training, evaluation, and red-teaming.
  4. Partner with Engineering teams to understand and build out supporting roadmaps.
  5. Drive tooling evolution, automation strategy, and active learning pipelines.

Skills

Required

  • MS in Computer Science, Statistics, Applied Math or a related field
  • 8+ years of people management of data scientists, statisticians, or other analysis-related teams
  • 10-12 Years in AI data operations or ML program leadership
  • Demonstrated experience leading large-scale annotation or data operations teams
  • Skilled at attracting new talent, as well as developing talent within the team and planning for succession
  • Builds a culture where values guide decisions, people are put first, and innovation drives quality results
  • Communicates with humility and curiosity, creating an environment where people feel safe to share feedback openly
  • Strong understanding of ML lifecycle, model evaluation metrics, and feedback loops
  • Proven track record building scalable quality systems in high-growth environments
  • Ability to influence cross-functional technical leaders and executives
  • Deep analytical mindset with comfort in ambiguity and rapid iteration environments

Nice to have

  • Experience designing RLHF or structured human feedback programs
  • Background in large language model evaluation and red-teaming
  • Familiarity with synthetic data strategies
  • Exposure to the software development lifecycle or internal tooling investments
  • Prior experience managing a data operations team

What the JD emphasized

  • 10-12 Years in AI data operations or ML program leadership
  • Demonstrated experience leading large-scale annotation or data operations teams
  • Strong understanding of ML lifecycle, model evaluation metrics, and feedback loops
  • Proven track record building scalable quality systems in high-growth environments

Other signals

  • leading large-scale annotation or data operations teams
  • building scalable annotation programs
  • operationalize auditing for training, evaluation, and red-teaming
  • drive tooling evolution, automation strategy, and active learning pipelines
  • develop and execute on automation and data augmentation strategies