Top Fintech Machine Learning Engineer Jobs

The VP, Quantitative Developer will develop algorithms for crypto markets while collaborating with traders and optimizing trading systems.

Oversee strategic development and execution of analytics and machine learning initiatives. Mentor teams, manage projects, enforce data governance, and collaborate cross-functionally.

Build and productionize data models and algorithms to improve tax accuracy, anomaly detection, and operational efficiency; design experiments, score risk and confidence, improve data reliability, and partner with Product, Engineering, and Ops to integrate ML-driven automation across the platform.

The Senior Machine Learning Engineer will build and operate ML systems end-to-end, focusing on production-grade ML platforms, feature pipelines, and MLOps practices while collaborating with cross-functional teams.

Lead data analysis projects using advanced statistical techniques and machine learning models. Develop predictive models, operationalize monitoring pipelines for LLM, and collaborate with teams on data-driven solutions.

Lead development and refinement of machine learning models for pricing and profitability. Collaborate with various teams, synthesize insights, and improve business outcomes while adhering to agile methodologies.

The Senior Machine Learning Engineer will design, build, and scale ML models and pipelines, support production efforts, and collaborate with other engineers and data scientists to deliver real business value using AI solutions.

The Machine Learning Engineer will develop and manage production ML systems for renewable energy deals, focusing on user feedback and model performance.

Individual-contributor ML engineer who designs, prototypes, and ships AI-powered newsroom and reader-facing tools. Build and deploy production systems leveraging LLM APIs and web technologies, collaborate with journalists and cross-functional teams, create evaluation frameworks, ensure responsible AI use, and iterate on MVPs based on newsroom feedback.

Design and implement AI-powered solutions for document extraction and financial reasoning, focusing on ML pipelines and application of LLMs.