Top Machine Learning Jobs in Ogden, UT

The Customer Success Engineer will lead deployments, serve as a technical advisor, and support customer engagement, focusing on product enhancements and user experience.

Research, draft, edit, and validate practitioner-facing US federal tax articles using AI tools. Ensure accuracy and currency, collaborate with data scientists, and align content with tax firm workflows and customer needs while helping build the content function.

OneSix is seeking motivated professionals for future opportunities in data and AI consultancy. Interested candidates should submit their resumes to stay in touch.

The Senior Director leads research in Application Platforms & AI, guiding clients in AI strategy and market trends, while producing critical research content and engaging with clients directly.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

Join Invoca's Talent Community to stay updated on job openings and to explore exciting career opportunities across various departments.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Lead vision, strategy, and roadmap for Fetch's referral growth engine. Own end-to-end referral lifecycle, build incentives, experimentation, AI-driven personalization, and cross-functional initiatives to drive MAU growth and durable network effects.

Lead product strategy and roadmap for a unified data platform, spanning ingestion, modeling, and an intelligence layer. Partner with engineering and data science to deliver cloud-native pipelines, curated analytic models, and ML productization. Drive governance, metrics, cross-functional alignment, backlog management, and Agile practices to maximize platform value for internal teams and clients.

Manage a portfolio of SaaS customers, build relationships, monitor usage, prevent churn, handle support and troubleshooting, identify upsell/renewal opportunities, and relay customer feedback to product and engineering.

Senior product engineer owning end-to-end product surfaces for a computer vision platform. Ship features from idea to production, prioritize roadmap, design UX details, integrate APIs, improve annotation and model-assisted labeling, and collaborate with engineering and users to drive product impact.

Design, develop, and evaluate conversational AI agents and generative AI products. Collaborate with AI scientists, ML engineers, and Responsible AI/Model Validation teams to ensure state-of-the-art, ethical solutions and support deployment and integration of conversational systems.

The Director, Strategy & Insights will enhance client performance using advanced analytics and machine learning, ensuring client satisfaction and achieving revenue goals through strategic planning and cross-functional collaboration.

As VP of Engineering, you'll lead the application engineering strategy and team, integrating AI capabilities into products while ensuring quality and execution across backend, mobile, and desktop platforms.

The Solutions Engineer will provide technical support for customers, ensure satisfaction, communicate with sales, and analyze customer needs for product enhancements.

As the Engineering Lead, you will guide product strategy, manage and mentor engineers, and ensure successful execution in product areas, focusing on machine learning and technical expertise across teams.

The Product Manager will lead product development, working with cross-functional teams, driving growth, and creating user experience frameworks.

The role focuses on leading editorial efforts to define industry narratives around energy infrastructure, translating regulatory changes into strategic content for executives, and influencing sales and positioning through high-impact communications.

The Hyperscalers and Commercial Lead will develop technology-driven business strategies, drive customer adoption, and manage end-to-end sales processes while working closely with cross-functional teams.

The Technical Product Manager will develop and manage the cloud infrastructure for AI, collaborating across teams to enhance AI solutions and service offerings.

Design, build, and operate production AI platform capabilities and agentic workflows. Collaborate on architecture, write production-quality backend code, mentor developers, troubleshoot production issues, and drive adoption of reusable AI frameworks, MLOps practices, and cloud-native intelligent services across a multi-tenant SaaS dental platform.

The Senior AI Engineer at RegScale designs and operates AI systems, ensuring reliability and performance while overseeing the data pipeline and compliance integration, alongside improving AI capabilities across the engineering organization.