Top Remote Machine Learning Jobs in St. Louis, MO

As a Machine Learning Engineer, you will design, develop, and deploy machine learning systems, collaborate on AI features, and ensure reliable production performance.

The Director drives the predictive modeling strategy, mentors others, leads initiatives, and advises on data strategy and innovation in credit risk and collections.

The role leads predictive modeling and machine learning initiatives, mentors team members, and drives innovations in data science for credit risk and operations.

Lead a team of ML engineers to deliver AI/ML solutions on AWS, focusing on practice strategy, operational excellence, and building partnerships.

As a Cloud Machine Learning Engineer at Hugging Face, you will build ML solutions leveraging cloud technologies, integrate models, design APIs, and contribute to documentation and community advocacy.

Develop, optimize, and deploy ML solutions to improve content strategy and performance at Netflix, collaborating with teams across analytics and engineering.

Machine Learning Systems Engineers will develop end-to-end 3D machine learning systems, optimize training pipelines, and improve model performance within a collaborative team.

Lead the design and execution of ML-based targeting products, improving advertiser outcomes while mentoring junior engineers and collaborating with cross-functional partners.

Lead the design and architecture of GNN and transformer-based multi-entity embedding generation for Reddit's recommendation systems, collaborating across teams and optimizing machine learning pipelines.

Drive AI/ML-powered personalized experiences on Pinterest by defining product vision, collaborating across teams, and launching new features to enhance user engagement.

The Senior Product Manager will develop AI tools, collaborating with research, engineering, and design to meet user needs and drive business value.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

Design and implement machine learning models to improve Risk and Fraud detection systems. Lead technical strategy and partner with operations to address rapidly evolving challenges.