Top Machine Learning Jobs in Ogden, UT

The Product Manager will contribute to product development, communicate with leadership, analyze market data, collaborate with engineers and designers, and oversee product positioning.

The Senior Product Manager leads the Cloud Infrastructure Entitlement Management product, balancing market needs with organizational strategy, engaging stakeholders, and managing the product lifecycle in a fast-paced environment.

In this leadership role, the Principal Architect develops and implements enterprise-wide data security strategies, focusing on AI and ML challenges, while mentoring teams.

The Senior AI Consultant will collaborate with leaders to identify automation opportunities, design proof of concepts, implement AI solutions, and ensure value creation through effective change management.

Lead and grow an engineering team to optimize borrower experiences, partnering with multiple departments to drive data-driven decisions and experimentation.

The GVP, Strategic Sales - East leads the east strategic sales team, managing 32 sales professionals, overseeing business processes, and enhancing customer relationships to drive sales growth.

The AI Product Sales Manager defines and executes sales plans, manages the sales pipeline, and develops client relationships in AI solutions within various sectors.

The Senior Data Scientist will optimize product performance through data analysis, collaborate with teams to provide insights, and support product initiatives.

Lead Compa's Applied AI team, overseeing ML projects and initiatives. Collaborate cross-functionally and ensure delivery of production-grade AI systems.

Manage advanced data analytics for credit strategies, optimize risk models, mentor a team, and oversee project completion in a remote-first environment.

The AI Engagement Manager will foster relationships with top partners, facilitate adoption of AI solutions, and analyze performance using BI tools.

The Sr. Product Designer will create user-centered mobile experiences for AI-supported mental health therapy. Responsibilities include designing workflows, collaborating with teams, and utilizing strong design skills in mobile applications.

As a Machine Learning Engineer, you'll enhance ML productivity, improve model deployment, and implement algorithms for credit decisioning systems.

Lead the Security & Risk department, overseeing cybersecurity and fraud prevention while implementing security automation and tools for innovation. Manage a skilled team, foster partnerships, and ensure physical security for employees and operations.

Lead research on large language models to address healthcare challenges, collaborating with teams to enhance model performance and ensure real-world applicability.

The role involves building computer vision models, researching deep learning methods, handling large datasets, and implementing MLOps best practices.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

Dandy seeks a Machine Learning Engineer to develop 3D computer vision models using SOTA methods, collaborate with product teams, and implement MLOps pipelines.

Lead a team to develop Dropbox's AI product, Dash. Focus on driving product revenue, operational agility, and mentoring team members. Utilize ML techniques and data-driven insights for decision making.

The Senior Machine Learning Engineer will develop AI workflows, collaborate with teams on models and pipelines, conduct research, mentor junior members, and innovate solutions for healthcare.

Lead and manage a team of machine learning engineers to develop AI-driven tools for clinicians, ensuring project success and team growth.

The Principal Product Manager will define and execute the product roadmap for the Data and AI Platform, collaborating with engineering and sales to develop AI-powered identity security solutions.

The AI Consultant supports AI implementation, collaborates with teams, conducts assessments, manages projects, and drives change management for AI strategies.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

Lead the architecture and management of AI/ML infrastructure using Kubernetes and Terraform, optimizing hybrid environments for performance and scalability.