Top Senior Machine Learning Jobs in Ogden, UT

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.

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.

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.

As a Senior Machine Learning Engineer, you will design and implement systems for ML and NLP, optimizing models and tools for Clover's healthcare solutions.

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.

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 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.

Lead technical pre-sales engagement: present Snowflake to executives and engineers, deliver demos and enterprise proofs-of-concept, design solutions, map customer architectures to Snowflake, collaborate with product and engineering, and close large deals while maintaining deep ML/generative AI and data platform expertise. Approximately 30% travel.

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.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

The Enterprise Account Executive will drive revenue growth by managing complex sales cycles, closing deals with Fortune 500 companies, and understanding both technical and business needs.

Lead pre-sales technical engagements for Conversational and Generative AI solutions, collaborate across teams, and design value-driven demos for enterprise customers.

The Principal Architect will lead AI/ML solutions, mentor teams, and collaborate with clients to design and deliver scalable systems using Google Cloud technologies, ensuring compliance with ethical standards.

The Regional VP of Sales drives sales for Lirio, focusing on healthcare systems. Responsibilities include pipeline generation, relationship building, and strategic sales management.

Pre-sales technical lead for federal accounts who builds and delivers AI/ML and GenAI demos, designs compliant solutions (FedRAMP/DoD IL/NIST/FISMA), supports pilots/proofs, advises on data readiness and security, and partners with sales to drive federal adoption.

The Data Science Manager will lead and mentor a team of data scientists, drive data-driven decision-making across Stripe, and collaborate with various stakeholders. Responsibilities include managing projects, recruiting, and contributing to broader data science initiatives.

This role leads Revenue Growth Management initiatives, linking data analytics with executive strategy to drive business growth through actionable insights and project management.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

As a Senior Data Scientist, you will apply machine learning and AI algorithms, conduct feature engineering, and collaborate with teams to optimize models and provide data insights.

Lead delivery of advanced analytics and investigative support for federal programs. Manage multiple concurrent projects, schedules, costs, risks, personnel, vendors, and stakeholder communications to ensure quality, timely contract-aligned deliverables.

Lead strategy and roadmap for DTNs upstream intelligence portfolio, especially Farm Intelligence. Conduct customer discovery, define product metrics, prioritize features, and partner with Engineering, Design, Data Science, and Commercial teams to deliver data-intensive, AI-enabled B2B SaaS products. Drive launches, adoption, and continuous optimization through experimentation, analytics, and stakeholder alignment.