Top Machine Learning Jobs in Ogden, UT

Lead the design and implementation of ML training systems, manage a team, promote engineering culture, and drive product development.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

As a Senior AI Engineer, you'll design and implement AI-driven solutions, focusing on full-stack development and production-grade applications while mentoring junior team members.

Lead planning, deployment, tuning, and operational support of CrowdStrike Falcon's AI/ML detection and response capabilities. Implement and optimize ML models, develop automation playbooks and Falcon API integrations, troubleshoot AI-related issues, support incident response and threat hunting, and deliver customer workshops and collateral. Up to 25% travel.

Lead data science initiatives to develop and deploy AI solutions that improve business outcomes. Collaborate with cross-functional teams to analyze data, create models, and evaluate performance.

The Analytics Lead will leverage data analytics to optimize credit strategies, monitor portfolio performance, and collaborate on credit policy with stakeholders across technical and non-technical teams.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Lead engineering teams to design and implement core voice AI APIs. Responsible for team management, project planning, technical strategy, and collaboration with research and product teams.

Lead the Creative Serving engineering team to define strategy, roadmap, and execution. Translate business goals into technical deliverables, collaborate with ML and product stakeholders, ensure high-uptime integrations with partner exchanges, provide technical guidance and feedback, enforce engineering best practices, balance short- and long-term priorities, and mentor engineers into future leaders.

Drive new business sales of Qualtrics Market Research Edge subscriptions to enterprise accounts. Develop account plans, build executive relationships, coordinate with SDRs and solutions consultants, craft ROI-based business cases, negotiate deals, and position AI/ML-enabled insights offerings to meet client needs and expand revenue within an assigned territory.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

The VP, Strategic Sales will lead enterprise sales efforts, focusing on Fortune 500 clients, developing relationships, and driving significant revenue through complex sales cycles.

Lead Pluralsight's curriculum strategy to identify and shape future skills; translate market and technology trends into a curriculum roadmap; align with product, GTM, and content production; measure portfolio performance with data; lead and develop curriculum directors and managers; define scalable frameworks and represent the company externally.

Build and maintain full‑stack, customer‑facing web experiences that improve borrower conversion. Deliver end‑to‑end features (frontend, APIs, microservices), monitor performance and reliability, partner with Product/Design/ML, run experimentation and personalization, and contribute to platform architecture and on‑call health.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

The Director of Product Management for ML Platform will own the product strategy and execution, mentor PMs, and collaborate with ML teams to enhance infrastructure and manage costs.

Lead planning, deployment, tuning, and operational support of CrowdStrike Falcon's AI/ML detection and response capabilities. Implement and troubleshoot AI-driven detection models, automation playbooks, API integrations, and threat-hunting for customers. Provide training, mentorship, and customer-facing collateral while optimizing detection efficacy and integrating Falcon into customers' security workflows.

Lead long-term technical strategy and execution across multiple teams, architecting and evolving foundational frontend/backend systems and platforms at massive scale. Drive AI/ML adoption, solve ambiguous, high-impact problems, remain hands-on in critical system design and implementation, and align senior leaders on roadmaps and engineering standards.

The role involves designing, building, and deploying computer vision models for vehicle damage detection, covering the entire ML lifecycle and collaborating across teams.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

The Engineering Manager, Data Science will lead a team to drive machine learning initiatives in AdTech, focusing on optimization and modeling strategies to enhance client success and operational efficiency.

Embed in Research to drive end-to-end delivery of STT/TTS model versions and features. Map dependencies and risks, run cross-functional programs, establish lightweight processes, and communicate status across Research, Product, DataOps, and Engineering to ensure timely launches.

Lead the design and implementation of critical Safety AI initiatives, focusing on real-time perception systems for edge devices and optimizing models for production deployment in safety-critical environments.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.