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# Machine Learning Engineer, Wallet Intelligence and Machine Learning

- **Company:** Apple Inc.
- **Location:** Austin, TX, United States
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Data Analysis, Apple Products, Cluster Analysis, Computer Programming, Distributed Data Store, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, Apache Spark, Ios Frameworks
- **Published:** July 20, 2026
- **Apply:** https://www.austinjobsite.com/job.asp?id=3327673860&tx=HT767THZ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

Are you motivated to protect users and their accounts while delivering the best possible customer experience? Come join the Wallet Intelligence and Machine Learning team, where we help secure users' digital lives across Apple's devices without sacrificing privacy. Machine Learning Engineers here build analytical solutions and think deeply about where they fit into a larger system, staying ahead of fraud and applying the best privacy-preserving and fraud-prevention methods available to make Apple products, and especially Apple Pay and Apple Wallet, the safest platform people can use., If you're energized by ambiguity, motivated by a meaningful mission, and the kind of person who digs beneath the surface and questions your own assumptions before forming a recommendation, we'd love to hear from you., * Experience with machine learning methods such as classification, clustering, and anomaly detection.

 * Strong programming skills 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 and succinctly 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., * Experience deploying machine learning in resource-constrained or real-time environments, such as on-device deployment, model compression, or optimizing for inference budgets.
 * Experience with distributed data and compute frameworks such as Spark, Ray, or Daft.
 * Familiarity with privacy-preserving machine learning techniques.
 * Background in fraud detection, risk modeling, or security-focused machine learning.
 * Familiarity with iOS development.
 * We're open to a range of specializations and are excited by candidates who bring a differentiating strength to the team, whether that's a research background, deep systems thinking, or expertise we don't yet have. Tell us what you'd add.

## Description

We are looking for a Machine Learning Engineer to help develop and launch on-device technologies that keep our users safe, working closely with engineering, security, program management, and business partners.


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