Top Machine Learning Jobs in Raleigh, NC

As a Senior AI/ML Engineer, you will develop and deploy Machine Learning models, collaborate with a cross-functional team, and work on building and maintaining machine learning pipelines with a focus on innovation and interdisciplinary teamwork.

As an AI/ML Engineer in the DSS team at Zifo, you will collaborate with global teams to design, develop, and deploy AI/ML solutions for the life sciences industry. Responsibilities include coordinating with stakeholders, mastering emerging standards, and supporting leadership in data science business growth.

The Senior Manager of Machine Learning Engineering oversees the productionization and deployment of ML models to optimize manufacturing costs and pricing. This role involves leading a team of engineers, ensuring high standards in model performance and scalability, collaborating with cross-functional teams, and driving continuous improvement in engineering practices.

The Staff, Machine Learning Engineer will develop and deploy machine learning models, collaborate across teams to implement statistical models, leverage advanced technical stacks for scalable AI solutions, integrate enterprise data sources, and harness LLMs to drive innovation in AI at Twilio.

As a Senior AI/ML Engineer at Twin Health, you will develop AI-powered systems, optimize ML models, and collaborate across teams to enhance member health outcomes. Your work will involve utilizing advanced techniques in reinforcement learning and deep learning to provide personalized health recommendations.

The Practice Director will lead the Data Engineering and AI/ML practice, managing customer engagements and focusing on Data Modernization. Responsibilities include strategic planning, team leadership, guidance on data solutions, and operational management while ensuring excellence and innovation in delivery.

The Sr. AI/ML Engineer III will analyze complex datasets, apply machine learning techniques, present results, and lead technical design and support for identity management systems. They will also engage with federal leadership, providing expertise in security architecture and data solutions, specifically in a cloud environment using AWS and graph data science techniques.

The Senior Big Data Engineer will develop scalable batch processing systems using the Hadoop ecosystem and manage Machine Learning pipelines. The role requires strong programming skills in Java and Python, knowledge of GCP for data processing, and extensive experience in engineering complex systems. The candidate should excel in remote collaboration and maintain effective communication with team members.

As a Sr. ML Ops Engineer, you'll develop and maintain scalable ML pipelines, automate workflows, monitor and optimize model performance, collaborate with teams, ensure compliance, and document ML processes and performance.

As a Senior Machine Learning Engineer, you will design and develop machine learning applications, conduct experiments, work collaboratively with engineers, engage with clients, and mentor project teams, focusing on practical AI solutions for clients.

Design and implement machine learning solutions for a Conversational AI platform and new product. Collaborate with cross-functional teams to architect scalable ML systems. Stay updated on the latest ML technologies and incorporate them into solutions.

As a Staff Software Engineer - ML, you will develop and manage relevance models to enhance user experience on Eventbrite. Collaborating with various teams, you will tackle machine learning, search ranking, and recommendations to ensure the right content is presented to users.

The Practice Manager for Data Science, AI, and ML will lead a team of experts to deliver professional services, ensuring successful customer engagements. Responsibilities include acting as a technical liaison, guiding teams through projects, educating clients on data science solutions, and supporting cloud migrations. The role requires building strong customer relationships and delivering training to ensure client and team knowledge.

The Technical Product Manager will collaborate with data science and machine learning engineers to develop models optimizing ad performance. Responsibilities include integrating ad infrastructure, communicating with stakeholders, monitoring KPIs, and leveraging insights for product decisions.

As a Staff Data Scientist at Coinbase, you will build advanced models, provide technical mentorship, and develop novel experimentation techniques to drive business value. Your role will involve creating sequential features based on user behavior and quantifying the impact of negative experiences on the platform.

The AI/ML Data Analyst will develop mathematical models and algorithms for the AI/ML initiative, analyze data models, review algorithms for performance, and troubleshoot field issues. They will also serve as a subject matter expert on AI tools and techniques, ensuring all business activities align with company policies.

The Machine Learning Engineer is responsible for developing, implementing, and productizing machine learning models for business solutions. Key tasks include model deployment, data preparation, collaboration with product teams, optimization, monitoring, and staying current with AI/ML trends.