Top Machine Learning Jobs in Raleigh, NC

The role involves developing and optimizing intelligent agents using large language models, collaborating with the team, and solving technical problems.

The role involves building and maintaining ML pipelines, optimizing workflows, and contributing to product strategy with a focus on usability.

Lead technical strategy and architecture for AI projects, manage client engagements, mentor engineers, and drive innovation in machine learning solutions.

Design and maintain production-grade ML systems, develop generative AI models, architect data pipelines, and collaborate with teams to solve business problems.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

Responsible for deploying and improving MLE solutions, building production data pipelines, and writing scalable machine learning systems while collaborating with teams to drive strategy and communicate results.

The Lead Data/ML Engineer will design and maintain scalable data pipelines and AI systems, ensuring data reliability and collaboration with product teams.

The Senior Product Manager will lead the strategy for an AI assistant, ensuring compliance and user satisfaction while coordinating with cross-functional teams throughout product development.

The Machine Learning Engineer will work on sensing and perception algorithms, deploying computer vision algorithms, and collaborating for code testing and evaluation.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

The Applied Scientist Intern will develop and deploy AI models, build ETL pipelines, and collaborate to enhance AI quality in legal tech.

The Staff Machine Learning Engineer will design, develop, and deploy scalable ML algorithms, lead experimentation, and collaborate across teams to enhance AI solutions.

Lead ML research and development, collaborating with engineers and clinicians to create enterprise-grade products and establish a research agenda while sharing insights through publications and presentations.

The Senior Machine Learning Engineer will develop ML infrastructure, deploy ML models, monitor performance, and mentor junior engineers. Collaboration with cross-functional teams is essential.

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.