Sr. Machine Learning Engineer - Finance

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and curiosity to your job and there's no telling what you could accomplish. Do you love thinking analytically? Just as our customers find value in Apple products, the Finance group finds value for both Apple and its shareholders. As a machine learning engineer in Finance, you’ll play an integral and global role in building the data foundations, services, and platforms used for delivering insights and automating decisions for Apple’s Finance organization. ## Description This role will require you to be collaborative by learning intra-team and business process in order to build infrastructure and services to enable an effective Machine Learning practice. You will help lead the charge by developing a strong ML Ops process in a dynamic Finance environment where you will deal with unique challenges specific to Finance organizations, such as SOX and regulatory compliance. Your ability to instill and proliferate strong software engineering practices into team data science and machine learning processes will be critical. ## Responsibilities Build and operationalize AI solutions in Apple Finance Partner with teammates and share expertise across teams Explain technical concepts to non-technical audiences Collaborate effectively with cross-functional teams Instill strong engineering practices into team machine learning processes Rapidly and reliably deliver value to the Finance organization ## Minimum qualifications Undergraduate degree (computer science, data science, finance, economics, accounting, or related business discipline) with seven years demonstrated experience Experience building data models and scalable pipelines using SQL and big data technologies, with expertise in data ops best practices Experience developing in Python while following DRY principles, modularity, and testing standards, with version control, code review. Experience applying ML algorithms for regression, classification, and anomaly detection; build generative AI and agentic solutions; implement MLOps/LLMOps including CI/CD, drift monitoring, and cloud platforms (AWS, GCP, Azure) Ability to explain technical details to non-technical audiences Understands and advocates version control, test driven development and strong CI/CD process ## Preferred qualifications Graduate degree (computer science, data science, math, quantitative finance, or similar discipline) with five years experience Previous experience working in a corporate finance, accounting, or supply chain organization Understanding of or ability to learn financial statements, P&L impact, high level accounting principles, SOX and tax compliance and month-end close process Experience with front end (.js experience)