Platform Engineer, Privacy Preserving ML
Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 16, 2026. Apple scores B on the Alion truth index.
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 great privacy to our users. 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, and are looking for an outstanding candidate to help us scale across Apple products.
Description
We are seeking an experienced platform learning engineer and to join our team building privacy-preserving technologies for measurement and machine learning. Successful candidates will need to have a strong technical background and interest or experience with backend development and deploying data-intensive systems. Strong interpersonal skills and the ability to influence and build consensus are crucial to success in this role. You will be working across a range of technologies, so adaptability to new problems and systems is a core skill.
Minimum Qualifications
0-2 years of industry experience with a Bachelor’s degree or equivalent experience in Computer Science or a related technical field.
Experience with differential privacy, secure multi-party computation, private federated learning, or PII redaction frameworks.
Experience architecting, deploying, and scaling data intensive systems.
Strong hands-on experience in SW development, with proficiency in one or more programming languages such as Python, Swift, and C++.
Experience building systems to orchestrate, automate, and harden data processing pipelines.
Strong problem-solving skills, creativity in finding effective solutions, and the ability to collaborate with teams across the company.
Preferred Qualifications
Passion for customer privacy.
Experience with differential privacy, secure multi-party computation, private federated learning, or PII redaction frameworks.
Experience with statistical techniques for A/B testing, distribution estimation, and sampling theory.
Experience with compliance, security protocols, and defense in depth to reduce vulnerabilities.
5+ years of industry experience.
Master's degree or PhD or equivalent experience in Computer Science, Software Engineering, or a related technical field.