Top Remote Artificial Intelligence Engineer Jobs in Denver & Boulder, CO

Lead the development of AI agents, monitor and optimize their performance, integrate them into workflows, and support company-wide AI initiatives.

As an AI Engineer II, you'll support AI feature development, participate in projects, assist in model implementation, and collaborate closely with team members to deliver AI-driven solutions in healthcare.

The AI Engineer III will build and implement AI systems for healthcare data, ensuring operational reliability and collaboration with stakeholders to achieve business objectives.

The role involves developing features for GitLab's AI-powered platform, advocating for quality improvements, and collaborating within a remote team.

Design and develop AI and machine learning models, optimize them, and collaborate with teams to integrate them with existing systems.

As an AI Engineer, you'll develop features, curate data, train models, evaluate performance, and lead technical initiatives in AI.

Join Zapier's AI Tasks team to design and build features for AI-based workflows, work with cross-functional teams, and own projects from concept to deployment.

Develop and implement predictive AI features to enhance user experiences, including natural language understanding and personalized AI agents for software development.

As an AI Engineer, lead the design and implementation of AI solutions in life sciences, focusing on model development, explainability, and collaboration with product teams to improve processing of complex data.

The Deep Learning/AI Engineer will develop AI systems for cybersecurity, implement deep learning algorithms, and enhance threat detection capabilities.

The AI Engineer will develop agentic AI solutions for automating decision-making, focusing on performance, compliance, and integration with federal systems while utilizing Generative AI and LLMs.

Lead the development of AI safety strategies for autonomous vehicles while ensuring compliance with industry standards, focusing on ML model validation and deployment in driving systems.

The Senior Software Engineer will own quarterly goals, lead the team through challenges, collaborate on product development, and ensure code quality, while also fostering team growth.

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.

Design, develop, and deploy AI and machine learning models. Collaborate with teams to integrate AI models and optimize for performance.

The Senior AI Engineer develops and deploys AI solutions, focusing on multi-agent systems and integrating them with enterprise workflows to deliver business outcomes.

The AI Engineer develops and deploys AI solutions, focusing on agentic systems, workflow automation, and integration while collaborating with senior engineers and clients.

The AI Engineer will design, develop, and deploy AI and machine learning models while collaborating with teams and optimizing model performance.

Research and implement state-of-the-art NLP and TTS technologies, focusing on creating high-quality AI speech models. The role involves leading projects and enhancing user experiences.

The role involves developing AI-driven features for observability tools, collaborating with cross-functional teams, and delivering scalable solutions.

The Senior Agentic AI Engineer will develop and deploy AI agents, automate workflows, ensure ethical AI use, and collaborate with team members on research and solutions integration.

As a Senior AI Engineer, you will develop AI systems for healthcare data, design AI components, mentor teammates, and contribute to hiring efforts.

Lead the development of an AI framework for endpoint security, collaborate with teams, optimize solutions, and ensure model efficiency across various platforms.

Lead the design and deployment of AI applications, collaborating with teams to integrate LLM models and ensure performance metrics are met, while fostering continuous improvement.

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