Machine Learning Engineer — Trust and Safety (Account Trust)
Apple
Summary
Description
Minimum Qualifications
- 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.
Key Qualifications
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.
Education & Experience
Additional Requirements
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.