Top Machine Learning Jobs in Dayton, OH

Lead product managers overseeing distribution and onboarding experiences, drive product execution, manage a team, and advocate for user needs.

Lead the development of AI-driven security workflows, integrate machine learning models, establish data pipelines, and mentor engineers.

Lead the design and optimization of programmatic bidding systems, collaborating with engineers and applying analytical methodologies to enhance performance.

The role involves designing and implementing scalable ML-based solutions, analyzing data patterns, and producing reports while staying updated on AI advancements.

As the Data Science Lead for Monetization, you'll shape monetization strategy, lead the data science team, and drive decision-making through measurement and experimentation.

Lead technical pre-sales engagements, design tailored solutions, demonstrate platform capabilities, assess customer needs, and expand relationships within life sciences and health technology.

The Vice President leads late-stage respiratory programs, manages clinical teams, ensures compliance, and oversees strategic execution in respiratory medicine trials.

The SVP of AI Innovation - Web Scraping will lead the development of AI-driven web scraping strategies, focusing on data acquisition, technology enablement, compliance, team building, and cross-functional collaboration for new data services.

The Product Manager will identify process improvements and innovations, utilize automation and AI, and manage the product lifecycle to enhance productivity and deliver business value.

The Director will lead Macmillan's corporate social media and community growth strategy, enhancing engagement and driving measurable growth across digital platforms through strategic content and analytics.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The Engineering Manager will lead the development of the Ad Platform infrastructure, ensuring high quality, efficiency, and accountability across systems while embedding AI and managing big data operations.

As an Applied Scientist, you will design and implement machine learning models, develop personalized systems, and enhance decision-making through AI technology to improve user experience and business operations.

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

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

The Lead Bioinformatics AI Scientist will lead AI and GenAI R&D initiatives to develop advanced clinical testing and genomic data analysis platforms, leveraging expertise in bioinformatics and machine learning.

The Director, Genomics Data will lead genomic data R&D, managing a team to advance data analysis, platform design, and commercialization efforts.

The Enrollment Advisor helps prospective patients through the onboarding process, providing information and support throughout their enrollment in Revero's program.

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

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

The role involves leading AI and data science initiatives, overseeing technical execution, fostering team development, and partnering with stakeholders to drive strategy.

The Data Scientist II will enhance marketing strategies through advanced measurement frameworks, statistical models, and cross-functional collaborations to drive revenue growth for Pinterest.

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

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

Lead the Opportunity Engine product development, managing cross-functional teams to drive advisor growth and improve client experiences using data and AI.