Machine Learning Engineer - Trust and Safety (Account Trust)
Apply NowCompany: Apple
Location: Austin, TX 78745
Description:
Summary
The Trust and Safety group at Apple is responsible for ensuring that users of Apple's services and products have genuine and safe experiences. Within Trust and Safety, our team ensures the protection of several systems, including Apple's account creation flows and iMessage spam. The solutions we deploy help us keep Apple ecosystem safe, while mitigating constant attack by external actors.
We are seeking a machine learning engineer who will strive to turn huge amounts of data into actionable insights that improve safe customer experience. Successful candidates will have a demonstrated history of self-directed research and investigations spanning sophisticated, interdependent systems that led to novel insights directly impacting well-defined success metrics.
Description
Success in this role is defined by your ability to:
Maintain a deep understanding of Apple's account types, services, and evolving protection systems.
Simplify complex systems and communicate technical concepts to non-technical audiences.
Analyze user behavior from diverse data sources, building narratives that explain fraudulent activity and attack methods.
Build strong partnerships to close data gaps and mitigate attack vectors.
Identify weaknesses, propose better fraud-fighting tools, and anticipate attacker adaptations.
This role requires exceptional collaboration across Data Science, Software Engineering, and Machine Learning Research.
You'll work with partner teams to develop strategic, long-term fraud prevention solutions while continuously enhancing your software engineering and machine learning expertise.
The Trust and Safety group at Apple is responsible for ensuring that users of Apple's services and products have genuine and safe experiences. Within Trust and Safety, our team ensures the protection of several systems, including Apple's account creation flows and iMessage spam. The solutions we deploy help us keep Apple ecosystem safe, while mitigating constant attack by external actors.
We are seeking a machine learning engineer who will strive to turn huge amounts of data into actionable insights that improve safe customer experience. Successful candidates will have a demonstrated history of self-directed research and investigations spanning sophisticated, interdependent systems that led to novel insights directly impacting well-defined success metrics.
Description
Success in this role is defined by your ability to:
Maintain a deep understanding of Apple's account types, services, and evolving protection systems.
Simplify complex systems and communicate technical concepts to non-technical audiences.
Analyze user behavior from diverse data sources, building narratives that explain fraudulent activity and attack methods.
Build strong partnerships to close data gaps and mitigate attack vectors.
Identify weaknesses, propose better fraud-fighting tools, and anticipate attacker adaptations.
This role requires exceptional collaboration across Data Science, Software Engineering, and Machine Learning Research.
You'll work with partner teams to develop strategic, long-term fraud prevention solutions while continuously enhancing your software engineering and machine learning expertise.