The SDS Machine Learning Engineer at Apple will focus on developing analytical solutions that enhance security, fraud prevention, and operational efficiency. This role involves employing predictive modeling and statistical analysis techniques to create end-to-end solutions that deliver measurable impact. The team is dedicated to pushing the boundaries of traditional machine learning methods while ensuring customer privacy. Collaboration with business teams and data engineers is essential to translate requirements into effective technical solutions.

• Education in a quantitative field such as Computer Science, Applied Mathematics, or Statistics, or at least 4+ years of relevant experience.
• Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection.
• Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark.
• Ability to implement data science pipelines and applications in a general programming language such as Python, Scala, or Java.
• Ability to comprehend and debug complex systems integrations spanning toolchains and teams.
• Ability to extract meaningful business insights from data and identify the stories behind the patterns.
• Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways.
• Creativity to engineer novel features and signals, and to push beyond current tools and approaches.

• Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions.
• Design data science approaches, applying tried-and-true techniques or developing custom algorithms as needed by the business problem.
• Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions.
• Ensure operational and business metric health by monitoring production decision points.
• Investigate adversarial trends, identify behavior patterns, and respond with agile logic changes.
• Communicate results of analyses to business partners and executives.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.