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Machine Learning Engineer – Trust and Safety – Account Trust
| Company | Apple |
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| Location | Cupertino, CA, USA |
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| Salary | $175800 – $312200 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Mid Level, Senior |
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Requirements
- Proven experience in anti-fraud (or similar) with at least two complex investigations in incomplete data environments, demonstrating initiative and measurable impact.
- 3+ years of experience with big data tools (SQL, Spark, Splunk, Python, Jupyter Notebook).
- Familiarity with machine learning algorithms including classifiers, clustering algorithms, and anomaly detection
- Experience collaborating across engineering and non-engineering teams.
Responsibilities
- 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.
Preferred Qualifications
- Experience with Python, Scala, Java, or similar, including relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Spark MLlib).
- 2+ years of industry software development experience using source control (e.g., Git).
- Hands-on experience implementing machine learning solutions (classifiers, clustering, anomaly detection).
- Advanced degree (MS/PhD) in a quantitative field (Computer Science, Statistics, Mathematics, Operations Research).
- Effective interpersonal, written, and verbal communication skills.
- Curiosity, integrity, and a passion for learning and enhancing the Apple customer experience.
