Top Remote Machine Learning Jobs in Ogden, UT

The role involves defining the vision and strategy of the Outreach AI Platform, prioritizing the roadmap, collaborating with engineering and data science teams, and engaging with customers to refine AI strategies.

Manage and mentor engineers, contribute to product and infrastructure, drive projects, and collaborate cross-functionally to enhance AI platforms.

Drive new enterprise customer acquisition and growth for Arize AI by prospecting, conducting discovery with AI/ML stakeholders, running POCs, and closing full-cycle SaaS deals. Build relationships, create sales plays, scope licensing, and collaborate internally to drive adoption and expansion.

As a Product Manager for Partnerships, you'll drive execution of partnerships by defining requirements, prioritizing tasks, and ensuring high-quality integration of partner-driven initiatives. You'll work across business development, engineering, and operations, managing multiple integrations effectively, and may require up to 30% travel for collaboration with partners and teams.

As a Senior ML Engineer for Payments, you will develop AI solutions for payment experiences, optimize transaction processing, and ensure system reliability while mentoring teammates and collaborating with cross-functional teams.

The Senior AI Engineer will develop AI solutions for incident management, collaborate cross-functionally, and enhance observability tools through iteration and ownership.

The Sales Development Representative will identify new business opportunities, qualify leads, and support sales strategies in the U.S. market, collaborating with sales and marketing teams to enhance lead generation and relationships.

The Senior Generative AI Engineer will design and deploy AI/ML solutions, focusing on Generative AI systems and their operational excellence across various sectors like R&D and Clinical Trials.

Design and implement production-grade ML systems for ICS/OT cybersecurity, build and optimize models (including NLP/LLMs), develop data pipelines and MLOps workflows, collaborate with data teams to deploy and monitor models in cloud and on-prem containerized environments, and troubleshoot production performance and resource issues.

The Applied Scientist AI/ML Intern will work on building data pipelines, finetuning LLMs, and deploying AI models in a collaborative team environment.

As a Senior AI/ML Engineer, you will design and develop advanced AI solutions for finance, focusing on ML and GenAI, ensuring compliance and operational efficiency.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

This role involves leading a perception team in developing algorithms for autonomous driving systems, supervising team members, and conducting research to enhance perception capabilities.

As the Lead AI Strategist, design and deploy advanced AI/ML models to optimize revenue and mitigate medical costs, impacting financial performance directly.

Lead the design and operation of Twilio's ML and data platform, architecting cloud-native pipelines and implementing MLOps best practices while mentoring engineers and collaborating across teams.

Manage and mentor a team of machine learning and data engineers, overseeing ML model development, data pipelines, and collaborating with product teams on technical requirements.

The Machine Learning Engineer will develop and optimize models for processing tax documents, mentor juniors, and collaborate across teams.

The MLOps Engineer will design scalable ML infrastructure, manage containerized environments, develop training pipelines, and implement CI/CD pipelines, ensuring model reliability and performance.

Develop and deploy AI agents, integrating them with external systems and optimizing performance in multi-agent environments. Collaborate with product managers to align agent capabilities with business needs, exploring technologies in Generative AI and LLM orchestration.

The Staff Machine Learning Engineer will lead ML initiatives, develop AI systems, optimize pipelines, and mentor team members to automate healthcare processes.

The Machine Learning Scientist will design causal inference models, build measurement pipelines, and collaborate with Finance & Product teams to optimize subscription pricing strategies at Netflix.

As a Machine Learning Scientist, you will build and enhance forecasting models for Netflix's subscription business, collaborate with various teams, and improve statistical forecasting methods while considering external market signals.

Lead ML strategy and standards as a senior individual contributor: define ML infrastructure, tooling, and lifecycle processes; establish monitoring and feature patterns; partner across platform, data, and product teams; mentor data scientists and ML engineers to scale reliable production ML systems.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

Design, build, and scale ML and Generative AI systems. Develop applications using ML architectures and monitor model performance.