AIML - Principal Machine Learning Engineer, Measurement

$207,800 - $378,700/Yr

Apple - Cupertino, CA

Full-time - Mid Level

Cupertino, CA

Computer and Electronic Product Manufacturing

About the position

The Privacy Preserving Machine Learning team at Apple is seeking an experienced engineer and technical lead to develop and implement privacy-preserving technologies for measurement and machine learning. This role involves leading cross-functional teams, designing end-to-end measurement systems, and communicating technical trade-offs to senior leadership. The ideal candidate will have a strong background in technical leadership and experience in deploying privacy-preserving systems, with a focus on collaboration and problem-solving.

Responsibilities

• 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 standards.
• Communicate system design trade-offs, 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.

Requirements

• Consistent track record of technical leadership and practical experience deploying privacy-preserving systems.
• Strong interpersonal skills and the ability to influence and build consensus across multiple teams and organizations.
• Outstanding technical judgment and collaboration skills with experience shipping large-scale differentially private production systems.
• Experience leading strategic technical projects with multiple partners and directing the work of other engineers or as a technical lead.
• Strong problem-solving skills and ability to work independently.
• Experience with differential privacy or private federated learning.
• BS in Computer Science, Electrical Engineering, or equivalent experience.

Nice-to-haves

• Real-world experience implementing privacy/trust/security measures in consumer products or services.
• Participation in public standards forums or academic publications in privacy and machine learning.
• 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

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Discretionary bonuses or commission payments
• Relocation assistance