Top Senior Machine Learning Jobs in Cincinnati, OH

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

As a Solutions Engineer, you will drive sales growth, support partnerships, and deliver AI-driven solutions while collaborating with various teams.

The Director of Adversary Engineering will define strategies for log management and security automation, lead the development of automated workflows, and optimize security systems using AI/ML techniques.

As a Principal Data Scientist, you'll design and deploy cutting-edge machine learning models to drive financial success for customers and guide technical teams.

Lead a team to develop groundbreaking technology combining NLP, big data, and AI to enhance digital communication and interaction.

Lead product strategy and development in cybersecurity, focusing on supply chain security solutions. Engage with customers and cross-functional teams to drive product innovation and performance metrics.

The GTM role focuses on increasing revenue through new sales and partnerships, understanding client needs, and communicating product value.

As a Senior Machine Learning Engineer, you will design and maintain ML systems for content recommendations, search, and spam detection, while augmenting user experience and system performance.

The Senior Product Manager will lead product initiatives, manage the product lifecycle, and ensure solutions meet customer needs while driving market growth and achieving KPIs.

The Senior Product Manager will lead the integration of machine learning into search relevance, defining product vision and collaborating with teams to enhance ecommerce search functionality.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

Drive delivery excellence and customer success by leading the architecture and implementation of AI/ML solutions while ensuring account growth and client engagement.

The position involves driving AI/ML product development for personalized experiences, partnering across teams, and launching impactful products.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

The Staff ML Platform Engineer will enhance Afresh's ML platform performance and scalability, collaborating with ML teams to improve systems and deploy models efficiently.

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

The Forward Deployed Engineer collaborates with clients to solve complex problems using technology, integrating systems, writing production code, and leading projects to deliver impactful solutions in areas like financial crime prevention and national security.

As a Senior Machine Learning Engineer at ZoomInfo, you will enhance core datasets through ML/NLP solutions, manage entity resolution tasks, and drive cross-functional impact by mentoring teams and collaborating on ML KPIs.

Senior AI/ML Engineer responsible for designing, building, and deploying AI/ML systems, mentoring teams, and leading cross-functional collaborations to drive AI solutions.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

Design and develop AI capabilities and scalable microservices. Collaborate to integrate AI models and ensure performance in cloud environments.

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

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.