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Apple Machine Learning Engineer — Trust Safety Account United States, California, Cupertino 146691242
07.04.2025
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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.
- 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.
- 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.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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