Finance Digital Transformation Senior Machine Learning Engineer

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 theres 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. nnAs a senior machine learning engineer in Finance youll play an integral and global role in building the platform data foundations and services used for transforming Finances organization.

Youll learn intra-team and business process to build infrastructure and services enabling an effective Machine Learning practice. You will help lead the charge by developing robust AIML-driven processes and extending scalable platforms to optimize financial operations in a dynamic environment. You will tackle unique challenges specific to Finance organizations including SOX compliance regulatory requirements cost variance analysis margin analysis and scenario modeling while driving automation and efficiency across end-to-end finance workflows. Your ability to instill and proliferate strong software engineering practices into team data science and machine learning processes will be critical.n

Extend and improve existing platform capabilities for generative AI agentic workflows and machine learning inference use casesnDrive SLO definition close observability gaps and strengthen operational posture across ML stacknDevelop and deploy frameworks for agentic AI including evaluation and knowledge managementnHarden CI/CD and MLOps practices with testing drift monitoring and deployment guardrailsnEnsure controls are robust auditable and scalable within Finance governance frameworksnCollaborate with delivery engineering pods to identify pain points and prioritize improvements

Bachelors degree (CS data science engineering or similar) with 7 years experiencenDemonstrated experience improving and extending existing AIML platforms and servicesnHands-on ML platform experience: feature stores registries experiment tracking and model servingnStrong debugging and operational instinctsnValues engineering standards; modularity testing version control and code review nCI/CD and MLOps experience strengthening existing pipelines; familiar with GitOps nProduction Kubernetes and cloud platform experience nWorking knowledge of ML algorithms; experience shipping generative AI and agentic solutions

Experience inheriting and modernizing legacy ML infrastructure without disrupting existing usersnLLMOps familiarity evaluation pipelines RAG infrastructure prompt versioning and production guardrailsnBackground in corporate finance accounting or supply chain; understanding of SOx Pu0026L and close processesnFront-end experience for extending internal tooling and platform UIs a plus