Top Remote Machine Learning Jobs in Dayton, OH

Seeking a Senior Full Stack .NET Developer to work on a social good project, with strong skills in C#, AngularJS, design, and UX. Requires 5+ years of experience.

The Data Scientist II will design, build, and deploy machine learning models and data products, translating business problems into data-driven solutions, while collaborating with various stakeholders and ensuring reliable, production-ready outcomes.

The Director of Global Advisory will provide expertise in fraud and financial crime, engage with customers, drive solutions, develop content for thought leadership, and represent BioCatch at events, while collaborating with sales and product teams.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

Join Trexquant as a Global Alpha Researcher to develop trading signals, implement research, and apply machine learning for alpha discovery.

The AI Solutions Lead will expand Quantiphi's business in key insurance accounts by managing executive relationships, developing account strategies, leading sales initiatives, and ensuring client satisfaction.

As an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

Lead a multidisciplinary team to design, deploy, and optimize ML-driven bidding systems and measurement for a nine-figure marketing budget. Drive experimentation, partner strategy, media-mix optimization, and end-to-end measurement while aligning Marketing, Analytics, Engineering, and Product to improve marketing ROI and scale performance.

Lead portfolio-level Data & AI strategy and technical governance for enterprise clients. Advise C-suite, drive architecture and modern data stacks, win high-value engagements, and scale engineering and data science teams.

Lead manufacturing process improvements for precision optical production: analyze data, reduce cycle time and costs, design/qualify tooling and automation, apply Lean/Six Sigma and AI-enabled analytics, maintain process documentation, partner cross-functionally, drive CAPEX and continuous improvement projects, and train production staff.

Serve as the technical lead in pre-sales for state, local, and education customers: run discovery, design POCs and workshops, deliver demos, map needs to Socure solutions, advise on fraud/risk/compliance, influence product, and mentor junior consultants.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

Lead the Interventions engineering pillar owning technical strategy and execution for early diagnosis, longitudinal care, and treatment. Scale data and ML infrastructure, improve clinical data accuracy, manage ML/LLM features, drive AI-assisted SDLC, and partner cross-functionally with Product, Data Science, and Clinical Operations to meet clinical performance goals.

The Customer Solutions Manager enriches client relationships by driving data adoption, providing analytics insights, and identifying growth opportunities. Responsibilities include client engagement, data storytelling, and advocating for client needs internally.

The Staff GenAI Backend Engineer leads engineering for intelligent routing systems, collaborates with teams to enhance customer support, and maintains architectural integrity in a high-availability environment.

The Engineering Manager will lead teams in developing and managing Blackbaud's Data & AI platform, focusing on scalability, security, and cost-efficiency.

The Machine Learning Engineer will build data-intensive products, deploy ML models, analyze datasets, and collaborate with product teams to enhance Nextdoor's platform.

The role involves developing and integrating AI features into Cribl's products, collaborating with teams, and maintaining operational efficiency.

Lead development of digital twin and simulation models for warehouse operations, deploy AI-driven decision systems, build forecasting and optimization models, validate experiments linking operational metrics to financial impact, and partner with engineers, operations, and external AI/academic partners to scale innovations across fulfillment networks.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

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.

Lead credit analytics for the Send Now Pay Later product: build and maintain credit policies, pricing models, vintage and NPV analyses, executive reporting, model integration and testing, and explore alternative data to optimize approval rates and portfolio health.

Lead fraud detection and mitigation for a conversational Send Now Pay Later product: define first-party fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, integrate ML and decisioning tools (Taktile), and coordinate SARs and compliance reporting.

Lead credit analytics for the Send Now Pay Later product: build and optimize valuation, vintage and NPV models; manage credit policies, portfolio monitoring, and NPL reporting; integrate and test scoring models with engineering/data science; and research alternative data to improve predictive performance.

Lead fraud detection and mitigation for a conversational BNPL product: define fraud typologies, analyze repayment/chargeback trends, own fraud KPIs, design policies, collaborate on ML models and decisioning workflows, and coordinate SARs with Compliance.