Top Machine Learning Jobs in Raleigh, NC

The AI & Machine Learning Director will lead machine learning projects, design data workflows, and utilize advanced data analysis and visualization to drive business insights.

The Applied Machine Learning Engineer will develop AI-driven solutions, focusing on backend systems, AI integration, model deployment, and MLOps best practices, while collaborating with cross-functional teams.

As a Senior Consultant II, you will integrate AI technologies into business applications, build scalable microservices, and deploy AI models in production environments.

As a Sr. AI/ML Engineer III, you will design and implement reinforcement learning algorithms, integrate them into simulation environments, and evaluate their performance. Collaborating with engineering teams, you will ensure the maintainability and transparency of AI components while communicating results and recommendations clearly.

Design and deploy machine learning models for personalized recommendations and search on Zillow's platforms. Collaborate with cross-functional teams to enhance user experience.

The Senior Product Manager will lead the strategy and execution of AI-driven features in a SaaS platform, ensuring high-quality user experiences and data-driven decisions while mentoring junior team members.

The Engineering Manager - Data & ML will redesign and scale Underdog's data and ML platform, establishing best practices, leading a team, and collaborating with cross-functional teams to optimize data systems.

As a Machine Learning Engineer, you will develop and deploy AI/ML solutions, collaborate with product managers and engineers, and improve learning experiences.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

As a Senior ML Ops Engineer, you'll build ML infrastructure, implement automated deployment, optimize model serving, and ensure production performance.

The Solutions Architect for AI/ML at Snowflake will advise clients on best practices for Data Science workloads, design solutions, and build ML pipelines. Responsibilities also include working hands-on with SQL and Python, maintaining technical expertise and collaborating with teams to improve products.

Design and deploy machine learning models for autonomous vehicles, focusing on data tagging, dataset curation, and model validation.

We're looking for an AI/ML Engineer to enhance our edge MLOps solutions, improve ML workflows, and support team development with strong technical expertise in Python and ML frameworks.

Join DICK'S Sporting Goods as a Senior Machine Learning Engineer, focusing on AI-driven search solutions that enhance decision-making and engagement across the organization.

The Practice Manager leads Data Science, AI, and ML projects, managing teams, fostering growth, and ensuring customer success through technical guidance and strategic business planning.

Lead the development of AI agents and infrastructure, collaborate with stakeholders, design APIs and SDKs, and advocate for best practices.

This internship focuses on clinical pharmacology and AI/ML modeling, providing experience in developing predictive models using clinical datasets.

As a Senior Machine Learning Engineer, you'll design and implement ML models, develop data pipelines, and collaborate on AI features at Mural.

The role involves developing AI-driven features for observability tools, collaborating with cross-functional teams, and delivering scalable solutions.

The Senior Power System Studies Engineer designs and applies AI/ML techniques for power system optimization, conducts simulations, and mentors junior engineers.

The ML Platform Engineer will develop and scale ML infrastructure, automate workflows, and collaborate with data scientists to deploy models efficiently in production.

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

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

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

The role involves fine-tuning machine learning models, designing datasets and pipelines, and ensuring product quality and safety for a new AI application.