Top Fintech Machine Learning Engineer Jobs

As a Machine Learning Engineer II, you will enhance AI systems for automating customer operations, develop evidence extraction pipelines, and collaborate with teams on model development and deployment.

The role involves partnering with data scientists and engineers to develop machine learning models, evaluate model risk in fraud detection, and translate complex data insights into business goals.

The AI Solutions Architect develops ML solutions, integrates them into systems, collaborates with stakeholders, and reviews code while maintaining technical architecture.

As a Staff AI Software Engineer, you'll develop and optimize scalable AI applications, manage deployment pipelines, and collaborate with cross-functional teams to drive innovative solutions.

The Applied Scientist will tackle various machine learning problems, enhance valuation systems, and deploy deep learning models while collaborating with cross-functional teams.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

Lead Gusto's AI/ML strategy, managing teams in Machine Learning Engineering, AI, and Risk Data Science. Ensure systems are reliable and impactful while fostering a culture of technical excellence.

Conduct ML and deep learning research to build, test, and deploy predictive models for trading. Collaborate with traders, researchers, and engineers to engineer features, preprocess data, prototype algorithms, and improve production research tooling to enhance trading performance.

As a Machine Learning Engineer in Fraud Risk, you'll build and maintain ML systems for fraud detection and anomaly analysis, ensuring robust performance and real-time decision making.

This role involves developing ML tools and frameworks, supporting data science environments, and leading projects from design to execution. Candidates need strong programming skills and a quantitative background.