Sr. Machine Learning Engineer - Finance

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. 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)