Top Machine Learning Jobs in Cincinnati, OH

Work with enterprise customers to identify high-value tabular ML use cases, design production-grade architectures, prototype solutions, lead deployments, coordinate cross-functional teams, and codify reusable deployment patterns to scale adoption of the NEXUS tabular foundation model.

The AI Engineer will design and build production systems, focusing on LLM integration, system reliability, evaluation frameworks, and high-quality product features while maintaining strong engineering practices.

As a Principal Product Manager, you'll lead product strategy, collaborate across teams, utilize data for decision-making, and partner with top executives to drive product success.

As a Software Engineering Intern, you will contribute to building features for user-facing products, APIs, and scalable services for machine learning. Responsibilities include crafting code, designing data pipelines, implementing tools, and enhancing technical documentation.

The role involves building predictive models for blockchain performance and user behavior, implementing solutions, and owning production prediction pipelines.

Lead end-to-end delivery of LOIS by owning the master program plan, coordinating cross-functional teams (engineering, product, design, ML, data, SRE, operations), resolving blockers and dependencies, establishing lightweight delivery infrastructure and tooling, partnering on release planning, and maintaining transparent status, risks, and accountability to deliver complex features to customers.

This role involves leading a perception team in developing algorithms for autonomous driving systems, supervising team members, and conducting research to enhance perception capabilities.

Lead supply chain analytics engagements: manage client teams, design data-driven solutions for demand forecasting, inventory and network optimization, drive key initiatives to closure, and provide thought leadership in supply chain analytics.

Lead Tekmetric's API product strategy and roadmap for the SaaS platform. Own API lifecycle (contracts, versioning, documentation), drive developer experience and adoption, identify integration opportunities, lead generative AI initiatives, perform user research and analytics-driven prioritization, collaborate across design/engineering/sales, train internal teams, and measure business impact.

The Data & Analytics team at Surescripts transforms healthcare data into actionable insights, collaborating with various stakeholders to support critical decisions across the healthcare ecosystem.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Senior individual-contributor responsible for owning and expanding strategic enterprise accounts by selling Nexis content, data, APIs, and AI-enabled solutions. Build executive relationships, create demand, develop account plans, displace competitors, lead complex negotiations, and coordinate cross-functional teams to drive multi-year revenue growth and enterprise adoption.

Lead the vision and execution of data product roadmap; translate business needs into epics and acceptance criteria; partner with data engineering and analytics; run agile ceremonies and manage backlog; champion data-as-a-product; scope and pilot AI/ML capabilities; present roadmaps and business cases to leadership.

Design, build, and operate core AI capabilities and reusable model integrations for an enterprise platform. Integrate foundation models into production, optimize performance and reliability, prototype new techniques, and support scalable backend services and distributed AI systems in collaboration with cross-functional teams.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

Work on-site with portfolio companies to design, prototype, and deliver full-stack digital and AI solutions. Lead discovery, deployment, and post-launch iteration, ensure security/compliance, resolve technical issues, mentor teams, and drive enterprise integrations and adoption. Frequent domestic travel and stakeholder management required.

Sell Litify's AI-driven legal operating platform to law firms and legal departments. Manage full upsell motions, consult on AI adoption, deliver high-level demos to C-suite, meet sales targets, and articulate ROI of autonomous agents and AI integrations.

Lead and mature Omada's enterprise privacy program, manage HIPAA compliance and incident response, embed privacy-by-design across products, conduct privacy risk assessments and vendor due diligence, advise on consumer privacy and AI governance, support interoperability/HIE participation, and deliver privacy training and guidance across the business.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Design and build scalable data engineering and AI agent governance capabilities across major cloud AI platforms. Develop ingestion, processing, ETL, observability, security, lifecycle management, and identity governance features. Evaluate emerging AI agent frameworks and interoperability standards, troubleshoot customer issues, document architecture and processes, and collaborate with engineering, security, compliance, product, and support teams. The role also involves improving distributed data systems, mentoring engineers, and leading technical initiatives.

Build, test, tune, and scale SIEM and data-lake detection rules mapped to MITRE ATT&CK. Manage detection-as-code through Git, pull requests, and CI/CD pipelines; reduce false positives and improve alert fidelity. Collaborate with threat intelligence, threat hunting, SOC, and data engineering teams. Use AI agents, LLM-assisted workflows, and AI/ML techniques to accelerate validation, coverage analysis, anomaly detection, and behavioral analytics. Monitor emerging threats and document detection logic and tuning decisions.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

Drive technical wins for enterprise financial institutions by scoping solutions, leading discovery (MEDDPICC), tailoring demos, building business cases, owning RFI/RFPs and POCs, and coordinating product/engineering to validate feasibility for fraud and financial crime prevention.