AIML Privacy-Engineering Rotation at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Jul, 26

Salary

0.0

Posted On

17 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Privacy Engineering, Software Engineering, Machine Learning, Differential Privacy, Private Federated Learning, System Architecture, Communication, Collaboration, Problem Solving, Policy Development, Data Privacy

Industry

Computers and Electronics Manufacturing

Description

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Apple delivers great features and privacy to our users. This unique role combines Privacy Engineering with hands-on software engineering work with the Privacy Preserving Machine Learning team. The Privacy Preserving Machine Learning team works with teams all across the company to provide tools and support for state of the art privacy-preserving measurement and machine learning. We are looking for an outstanding candidate with a strong interest in privacy in practice to take on this unique role. DESCRIPTION We are seeking an experienced engineer and privacy advocate to build privacy-preserving technologies for measurement and machine learning and guide policy and product decisions to uphold Apple’s industry leading privacy bar. Successful candidates will need to have strong interpersonal skills and the ability to influence and build consensus and work across multiple teams and organizations on a regular basis. MINIMUM QUALIFICATIONS Passion for customer privacy. Strong collaboration, communication, interpersonal, and organizational skills. Strong software engineering skills and 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. 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.

Responsibilities

The role involves building privacy-preserving technologies for measurement and machine learning while guiding policy and product decisions. You will collaborate across multiple teams to implement tools that uphold Apple's privacy standards.