Top Fintech Machine Learning Engineer Jobs

As an Applied Machine Learning Engineer, you will develop AI and ML models to improve healthcare outcomes. Collaborate with teams to implement and optimize machine learning techniques and algorithms.

Manage financial markets risk portfolio by applying statistical and machine learning models to optimize forecasting and decision-making. Collaborate with cross-functional teams to provide actionable insights.

As a Staff Machine Learning Engineer, you'll enhance credit products through advanced modeling techniques, data analysis, and ML operations, supporting robust decision-making processes.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.

The Principal Engineer, AI/ML Architecture will define the technical direction for Coupa's AI platform, focusing on model training, evaluation, safety standards, and mentoring a team of ML and data engineers.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

Contribute to machine learning model design, training, and evaluation for fraud detection. Communicate findings, develop metrics, and support production ML workflows while ensuring compliance and model governance.

The role involves engineering and deploying AI agents, collaborating with teams on solutions, and managing data flows. The position requires deep expertise in ML technologies and frameworks.

The Principal ML/AI Engineer will shape the AI vision, prototype AI systems, and architect an AI-ready technical stack while mentoring teams and collaborating with executives.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.