Finance Digital Transformation - Senior Machine Learning Engineer

You’ll 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. Minimum Qualifications Bachelors degree (CS, data science, engineering, or similar) with 7+ years experience Demonstrated experience improving and extending existing AIML platforms and services Hands-on ML platform experience: feature stores, registries, experiment tracking, and model serving Strong debugging and operational instincts Values engineering standards; modularity, testing, version control, and code review CI/CD and MLOps experience strengthening existing pipelines; familiar with GitOps Production Kubernetes and cloud platform experience Working knowledge of ML algorithms; experience shipping generative AI and agentic solutions Preferred Qualifications Experience inheriting and modernizing legacy ML infrastructure without disrupting existing users LLMOps familiarity — evaluation pipelines, RAG infrastructure, prompt versioning, and production guardrails Background in corporate finance, accounting, or supply chain; understanding of SOx, P&L, and close processes Front-end experience for extending internal tooling and platform UIs a plus