Top Machine Learning Jobs in Raleigh, NC

Design and build ML infrastructure components for autonomous vehicles, ensuring scalability and robustness for high-volume data processing and model training.

The Staff AI/ML Engineer will design and build AI-powered services, develop machine learning models, and optimize workflows, collaborating across teams to deliver quality solutions.

As an ML Solutions Architect, design, implement, and lead machine learning solutions for Conversation AI, collaborating with cross-functional teams to address complex business challenges.

The Senior Machine Learning Consultant designs and develops machine learning solutions while mentoring team members and collaborating with clients. Responsibilities include conducting R&D on AI/ML models, optimizing model performance, and ensuring adherence to ethical AI practices.

As a Staff Machine Learning Engineer, optimize card pricing models, lead ML lifecycle, collaborate with experts, and enhance predictive features.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.

As Principal Engineer, lead the development of AI agent systems for ML infrastructure. Oversee team management, architectural vision, and technical contributions while ensuring projects meet productivity metrics.

The Senior Machine Learning Engineer will design and implement high-performance CTR and CVR prediction models, refine systems for user behavior modeling, and ensure model reliability through performance monitoring while engaging with stakeholders.

Design and implement high-performance CTR and CVR prediction models, ensuring reliability and quality while collaborating with team leads on project direction.

Lead the optimization of inference systems, guiding a team to enhance model performance, drive innovation, and mentor performance engineers in a high-growth environment.

The role involves designing and implementing distributed systems for batch inference workloads, creating developer-friendly APIs, and fostering engineering excellence.

Drive the development of AI solutions for payments, ensuring low latency and high reliability, while mentoring teams and collaborating cross-functionally.

The Senior Software Engineer will own large-scale data mining workflows, improve ML products through high-quality datasets, and analyze model performance across driving scenarios.

As a Staff Machine Learning Engineer, you will develop scalable data infrastructure, manage ML workflows, and collaborate with stakeholders to optimize data usage and build automated processes.

Lead AI and machine learning projects, create workflows and models, analyze data from diverse sources, and present insights to non-technical audiences.

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

As a Machine Learning Customer Success Engineer, you'll assist users with ML workflows, manage customer relationships, and contribute to product development at Voxel51.

The role involves designing scalable AI solutions, managing large-scale AI deployments, building client relationships, and delivering presentations. Requires experience in MLOps and knowledge of ML ecosystems.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

As a Research Intern, you will work on AI/ML projects, contributing to the development of the Nebula LLM and applying machine learning techniques to real-world problems.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

The ML Engineering Intern will contribute to the Nebula LLM development, tackle machine learning challenges, and gain hands-on experience in AI and language technology.

As an AI/ML Ops Engineer, you will architect and operate ML pipelines, automate CI/CD processes, and collaborate with cross-functional teams to enhance engineering productivity.

Design and build infrastructure for ML model training and deployment. Collaborate with teams and monitor performance using AWS tools. Focus on reliability and efficiency in high-availability environments.