About The Position
Join the Wallet Intelligence and Machine Learning team at Apple, where you will help secure users' digital lives across Apple's devices, including Apple Pay and Apple Wallet, without sacrificing privacy. This mission-driven team develops on-device machine learning models that run directly on users' devices to protect them from fraud, adhering to exceptionally high privacy standards. The work is applied and pragmatic, requiring models to run in real-time and in the background on the device without impacting performance. You will anticipate fraud rather than just react to new patterns, requiring a proactive approach and deep thinking. This role offers the opportunity to take ownership of a problem area, gain a system-wide understanding of where models fit, and apply expertise in machine learning in an innovative and fast-moving environment. The ideal candidate is energized by ambiguity, motivated by a meaningful mission, and possesses a deep-diving, questioning mindset.
Requirements
- 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.
Nice To Haves
- 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.
- A research background, deep systems thinking, or expertise the team does not currently possess.
Responsibilities
- Develop and launch on-device technologies that keep users safe.
- Work closely with engineering, security, program management, and business partners.
- Design machine learning models within real-world constraints such as model size, inference budgets, and memory.
- Anticipate fraud rather than react to new patterns.
- Take ownership of a problem area.
- Build a system-wide understanding of where models fit.
- Apply expertise in machine learning in an innovative and fast-moving environment.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
