Apple · Cupertino

AIML -Sr. Machine Learning Engineer, Measurement

(f/m/d) · 1/15/2025

Description

We are seeking an experienced engineer and technical lead to build privacy-preserving technologies for measurement and machine learning. IN THIS ROLE YOU WILL: Lead multi-functional and cross-org teams deploying innovative privacy-preserving technologies for measurement and machine learning. Design, develop and deploy end to end measurement systems with high utility that meet Apple’s industry-leading privacy bar. Communicate system design tradeoffs, privacy risks and potential mitigations to senior leadership to drive decisions. Guide the development of data collection systems that enable training and evaluation of generative AI systems while preserving privacy. Successful candidates will need to have a consistent track record of technical leadership and practical experience deploying privacy-preserving systems. Strong interpersonal skills and the ability to influence and build consensus and work across multiple teams and organizations on a regular basis.

Qualifications

  • Outstanding technical judgment and collaboration skills and experience shipping large-scale differentially private production systems.
  • Experience leading strategic technical projects with multiple partners and directing work of other engineers or as a technical lead.
  • Strong collaboration, communication, interpersonal, and organizational skills.
  • Ability to solve complex problems independently.
  • Experience with differential privacy or private federated learning.
  • BS in Computer Science, EE or equivalent experience.

Preferred Qualifications

  • Real-world experience implementing privacy/trust/security measures which have shipped in a consumer product and/or service.
  • Participation in public standards forums or academic publications in privacy and machine learning strongly preferred.
  • Passion for customer privacy.
  • Ability to analyze systems’ architectures for privacy impact.
  • Ability to learn and research new technologies and use-cases rapidly, assess privacy exposures, and suggest mitigations.

Benefits

Application

View listing at origin and apply!