Senior Privacy Engineer, Intelligence (user Privacy)

Apple Apple · Big Tech · Cupertino, CA +1 · Software and Services

Senior Privacy Engineer focused on providing privacy guidance for machine learning and generative AI infrastructure at Apple. This role involves reviewing features, auditing products, guiding the roadmap of privacy technologies like differential privacy and private federated learning, and developing privacy-preserving data collection methodologies for AI systems.

What you'd actually do

  1. Review features to identify privacy exposures and partner with teams to design mitigations.
  2. Audit new products to identify bugs in development, and review customer data collected by engineering teams to drive decisions for privacy impact.
  3. Communicate privacy risks and potential mitigations to senior leadership to drive decisions.
  4. Guide the development of data collection systems that enable training and evaluation of generative AI systems while preserving privacy.
  5. Partner with cryptographers and technical experts in SWE and AIML to develop our roadmap for privacy technologies, and provide guidance to engineers and leaders on the right privacy technology to use when developing new features.

Skills

Required

  • BSCS or equivalent experience
  • Experience with foundation models, including training and evaluation
  • Experience with differential privacy or private federated learning
  • Experience conducting privacy reviews

Nice to have

  • Passion for customer privacy
  • Strong collaboration, communication, interpersonal, and organizational skills
  • Ability to learn and research new technologies rapidly, assess privacy exposures, and suggest mitigations
  • Ability to analyze systems’ architectures for privacy impact
  • Ability to solve complex problems independently
  • Programming experience

What the JD emphasized

  • privacy guidance
  • privacy preserving data collection methodologies
  • evaluation of AI systems
  • differential privacy
  • private federated learning
  • foundation models
  • training and evaluation
  • privacy reviews

Other signals

  • privacy-preserving data collection
  • differential privacy
  • private federated learning
  • foundation models
  • generative AI infrastructure