Senior iOS Software Engineer

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 is committed to delivering exceptional features and prioritizing user privacy. The Privacy Preserving Measurement & Machine Learning team develops state-of-the-art privacy-enhancing technologies for privacy-preserving measurement and machine learning. We are seeking an exceptional candidate to join our team contributing to iOS.

We are looking for an experienced software engineer to join our team and help us develop privacy-preserving technologies for measurement and machine learning.\n\nSuccessful candidates must possess a strong technical background and experience in iOS development, particularly in designing privacy-preserving features. Strong interpersonal skills and the ability to influence and build consensus are essential for success in this role. Since you'll be working with various technologies, adaptability to new challenges and systems is a fundamental skill.

Proficiency in one or more object-oriented programming languages such as C++, Objective-C, Swift.\nIndustry experience of iOS development, or experience of development on other embedded systems.\nProficiency in problem-solving, coupled with creativity in identifying effective solutions, and the ability to collaborate effectively within a cross-functional team.\n2+ years of industry experience with a Bachelor's degree or equivalent experience in Computer Science or a related technical field.

Passion for protecting customer privacy.\nKnowledge of basic privacy, security and cryptographic principles.\nExperience with differential privacy, secure multi-party computation, trusted compute environment or private federated learning.\nAbility to analyze system architecture and assess privacy & security impacts and suggest mitigations.\nExperience with training, evaluating, and deploying machine learning models to production.