Top Financial Services Machine Learning Engineer Jobs in New York City, NY

The role involves leading a team to develop machine learning models for personalized customer experiences, leveraging large datasets and advanced techniques, while collaborating with cross-functional teams.

The role involves partnering with cross-functional teams to build machine learning models and leverage technologies to analyze large datasets for marketing intelligence.

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.

The intern will utilize machine learning and statistics to extract patterns from data, implement algorithms, back-test models, and communicate findings effectively.

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 role involves developing AI and ML solutions, collaborating with teams to enhance client experiences, and ensuring proper model lifecycle management.

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.

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.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

As a Software Engineer (AI), you will design and implement AI systems, manage backend services, and collaborate closely with teams. You need extensive experience with LLMs and backend technologies.