On-Device Fraud ML Engineer - Privacy-First

Apple Inc.; Cupertino (CA); On-site; USD 167,000 - 278,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Discounted Apple products

Educational expense reimbursement

Job summary

Apple Inc. in Cupertino, CA seeks a Machine Learning Engineer for Wallet Intelligence and Machine Learning to develop on-device ML solutions that protect users’ accounts while preserving privacy.

You’ll work across teams to design real-time models that run efficiently on devices, and support Apple Pay and Apple Wallet. You will translate security needs into scalable ML systems, balancing accuracy, latency, and memory constraints while maintaining a strong privacy standard.

Qualifications

• Experience with machine learning methods such as classification, clustering, and anomaly detection.
• Proficient in one or more languages such as Python, Scala, or Java.
• Experience processing and analyzing data at scale using distributed data or compute frameworks.
• Ability to communicate the results of analysis clearly to a range of audiences.
• Experience delivering results on ambiguous, loosely defined problems, working with others.
• Rigorous analytical thinking, including the ability to question assumptions, reason through a problem, and justify a recommendation with sound evidence.

Responsibilities

• Take end-to-end responsibility for translating customer and security needs into machine learning solutions, from framing the problem through feature engineering, model development, training, evaluation, and reporting.
• Design and deliver models that operate within real-world constraints, balancing accuracy against latency, model size, and on-device compute budgets so that protection never comes at the cost of the user experience.
• Build and share a system-wide understanding of where our models fit into the user journey and the fraud-risk journey, and use that understanding to anticipate problems rather than react to them.
• Uphold and advance a high standard for user privacy in everything you build.
• Partner across software engineering, security, program management, and business teams to define problems, align on solutions, and communicate results clearly to both technical and non-technical audiences.
• Share your thinking openly, welcome scrutiny of your own ideas, and build trust with the people you work with.

Skills

Analytical thinking

Communication skills

Ambiguity tolerance

Collaborative teamwork

Tools

Python

Scala

Java

Spark

Ray

Daft

Job description

Apple Inc. in Cupertino, CA seeks a Machine Learning Engineer for Wallet Intelligence and Machine Learning to develop on-device ML solutions that protect users’ accounts while preserving privacy.

You’ll work across teams to design real-time models that run efficiently on devices, and support Apple Pay and Apple Wallet. You will translate security needs into scalable ML systems, balancing accuracy, latency, and memory constraints while maintaining a strong privacy standard.