Top Machine Learning Jobs in Raleigh, NC

Lead the design, development, and implementation of machine learning products, creating data pipelines and maintaining production stability.

The Staff Machine Learning Engineer will design and deploy ML models, build real-time model APIs, and collaborate across teams to drive user growth and revenue through AI/ML solutions.

The Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.

As a Staff ML Engineer, you will develop and deploy machine translation models, collaborating across teams to enhance Airbnb's translation capabilities and improve global guest experiences.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

Develop and deploy ML models for personalization and optimization, analyze performance, and collaborate with product teams to enhance user experiences.

Design, develop, and deploy machine learning systems, improve ML infrastructure, and partner with stakeholders to enhance data science workflows.

The role involves building scalable AI features, optimizing machine-learning pipelines, evaluating LLM outputs, and ensuring compliance with data governance standards.

As a Machine Learning Engineer, you'll build scalable ML systems for personalized recommendations, collaborating with data scientists and cross-functional partners.

The Senior Machine Learning Engineer will develop ML platforms, optimize model lifecycles, lead initiatives, and maintain code quality, collaborating with Data Science teams.

Lead the development of advanced recommendation systems and ML pipelines. Collaborate with cross-functional teams to enhance user engagement through optimization of machine learning models at scale.

Lead the design and development of AI solutions, optimize algorithms, collaborate with teams, and develop advanced models to drive business insights.

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.