Top Remote Machine Learning Jobs in Raleigh, NC

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Senior Software Engineer will develop ML training pipelines, maintain cloud systems, and optimize the ML lifecycle for dental products.

Lead the machine learning and personalization efforts at Babylist, managing a team focused on enhancing product recommendations, search, and revenue through ML initiatives.

The Senior ML Ops Engineer will build and maintain infrastructure for AI/ML at scale, manage machine learning models, and support team initiatives while ensuring code quality and engineering standards.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

Join Wasabi as an AI Engineer intern to build scalable machine learning solutions. Responsibilities include maintaining ML pipelines, model integration, and collaboration with various teams to drive AI initiatives.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The Senior Technical Program Manager will oversee the delivery of complex projects related to Application Modernization, working closely with multidisciplinary teams, driving programs forward, and balancing product goals with engineering constraints.

The Head of Consumer Product will create engaging experiences using relational AI, focusing on user well-being rather than metrics like engagement. Responsibilities include product strategy, user research, gamification, and community building.

Lead AI/machine learning innovations and advanced analytics for new vehicles. Develop statistical models for pricing and valuation, guiding experiments and communicating insights.

The Senior Data Scientist will design and implement data-driven initiatives, optimize product offerings using AI/ML, and collaborate with engineers on scalable solutions.

The Engineering Manager will lead a team of Data Scientists and ML Engineers to build a Dispatch Optimization platform, focusing on model deployment and operational excellence.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

Lead and manage a team of engineers in developing Affirm's Fraud Decisioning System, focusing on innovation and cross-functional collaboration with various stakeholders.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

As a Machine Learning Intern, you'll prototype and evaluate ML systems, collaborate with teams, and analyze large datasets to improve user experiences.

As Growth Marketing Lead, you'll drive scalable customer acquisition through optimizing paid marketing channels, beginning with Google, and potentially transition into leadership as strategies scale.

The Senior Applied AI/ML Scientist will lead the design and deployment of AI solutions, collaborate on impactful features, and enhance product capabilities by leveraging advanced AI and ML techniques.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.