As a machine learning engineer in Finance at Apple, you will play a crucial role in developing data foundations and platforms that deliver insights and automate decisions for the Finance organization. This position requires collaboration with various teams to build effective machine learning infrastructure while addressing unique challenges related to finance, such as regulatory compliance. You will also be responsible for establishing strong ML Ops processes and promoting software engineering best practices within the team. Your analytical thinking and technical expertise will be essential in driving innovation and efficiency in financial operations.

• Undergraduate degree in computer science, data science, finance, economics, accounting, or a related business discipline with seven years of demonstrated experience.
• Experience building data models and scalable pipelines using SQL and big data technologies.
• Expertise in data ops best practices.
• Proficiency in Python while adhering to DRY principles, modularity, and testing standards.
• Experience applying ML algorithms for regression, classification, and anomaly detection.
• Familiarity with MLOps/LLMOps including CI/CD, drift monitoring, and cloud platforms such as AWS, GCP, or Azure.
• Ability to explain technical details to non-technical audiences.
• Graduate degree in computer science, data science, math, quantitative finance, or a similar discipline with five years of experience.
• Previous experience working in a corporate finance, accounting, or supply chain organization.
• Understanding of financial statements, P&L impact, high-level accounting principles, SOX and tax compliance, and the month-end close process.
• Experience with front-end technologies, particularly JavaScript.

• Develop data foundations and services for delivering insights in the Finance organization.
• Collaborate with intra-team and business processes to build effective machine learning infrastructure.
• Lead the development of strong ML Ops processes in a dynamic finance environment.
• Instill and promote strong software engineering practices within the data science and machine learning teams.
• Address unique challenges specific to finance organizations, including regulatory compliance.

• 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.