Top Machine Learning Jobs in Dayton, OH

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.

Lead the design and implementation of advanced ML systems at Airbnb, mentoring engineers and shaping concepts into impactful products.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

Lead mobile app attribution strategies, collaborating with teams across engineering and data analytics to optimize performance and feature implementation.

Develop and implement messaging and positioning for AI products, create marketing content, lead go-to-market strategies, and analyze market research.

Develop and optimize machine learning systems for Yahoo News, collaborate with teams to enhance user experience and editorial tools.

The Software Developer Principal is responsible for architecting and delivering enterprise-grade products on SAP S/4HANA, driving AI adoption, and ensuring scalable, secure solutions while providing technical leadership and mentoring.

Own and close enterprise customer deals, develop expansion opportunities, educate customers on AI architectures, engage with multiple stakeholders, and collaborate with product and engineering teams.

The role involves reviewing AI-generated legal documents, providing structured feedback, and evaluating writing quality to improve AI models used in legal contexts.

The Principal ML/AI Threat Engineer will design and implement scalable threat intelligence systems, focusing on adapting ML models for threat detection and attribution from DNS telemetry.

The Senior Principal Product Manager will define the product strategy for ExtraHop's RevealX platform, focusing on enhancing SOC workflows and leading cross-functional execution while mentoring peers and aligning product vision with business goals.

The role involves building end-to-end modeling pipelines, developing models, delivering insights to stakeholders, and collaborating with a technical team in a fast-paced environment.

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

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

Lead the development and execution of ML platform strategies, manage a high-performing team, and enhance 3D deep learning applications.

The Staff Platform Manager will define the strategy for post-transaction experiences related to suspensions, appeals, and account actions. Responsibilities include managing product vision, improving customer experience, mitigating risks, and collaborating across teams to develop effective enforcement strategies.

The Senior Product Manager will advance fraud detection capabilities, manage product lifecycles, develop requirements, and collaborate with engineering and data science teams.

The VP of AI will lead the integration of AI into products, drive strategy for AI initiatives, and ensure responsible implementation across the organization.

The role involves managing data to uncover insights, developing predictive models, and bridging clients with data intelligence within the context of evolving market research methodologies.

The AI Application Engineer will design and deploy AI systems, collaborate with teams, implement Generative AI solutions, and promote continuous learning in AI practices.

As a Senior Fullstack Engineer, you'll architect and build a high-concurrency auction engine, leveraging AI for enhanced user experiences and system reliability.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Lead design and execution of an Operational Readiness Verification (ORV) framework for AV operations: define safety gates, run pre-launch audits and red-team exercises, own safety cases and RCA processes, verify mitigations, and drive safety culture and reporting with clients and cross-functional teams.

Lead development of AI-powered solutions, architect large language models, capture domain knowledge, and deliver client-focused insights. Manage a team to integrate AI capabilities across products.

Lead the development of the Clinical Genomics Workbench, overseeing product strategy, migration, market intelligence, and global team management to enhance market presence and ensure successful platform transition.