Top Machine Learning Engineer Jobs in Denver & Boulder, CO

The Staff Machine Learning Engineer will lead the development of AI solutions, ensure project delivery, and manage technical teams while interfacing with customers. Responsibilities include designing data pipelines, overseeing machine learning model development, and facilitating customer engagement.

As a Senior AI/ML Engineer, you'll enhance developer productivity by leading CI solutions, mentoring engineers, and implementing scalable systems.

The Staff Machine Learning Engineer will define technical strategies, design ML models for document processing and risk assessment, and build scalable ML systems to protect Coinbase users' funds.

The Staff Machine Learning Engineer will utilize AI models, mentor team members, and enhance automation solutions across Coinbase's operations, focusing on machine learning to solve complex challenges.

As a Machine Learning Engineer in the Risk AI/ML team, you will design and deploy sophisticated AI/ML models to prevent fraud and improve risk detection processed while leading technical strategies and mentoring team members.

Lead the design and implementation of AI/ML models for risk and fraud detection at Coinbase. Collaborate with teams to develop scalable systems, mentor engineers, and ensure effective AI/ML solutions align with company goals.

The role involves developing ML models to enhance security measures against fraud and scams, collaborating across teams, and deploying sophisticated AI solutions on the self-service ML platform.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

The Machine Learning Engineer will build and deploy data products, collaborate cross-functionally, improve customer experiences, and mentor others in AI methods.

Develop and deploy machine learning models for risk assessment, collaborating with teams to enhance Gusto's product offerings while ensuring model performance and reliability.

Design and develop scalable AI/ML solutions while mentoring teams and collaborating with cross-functional partners to enhance customer experience through data-driven insights.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

Develop and deploy AI-driven solutions, collaborate with teams, and communicate technical concepts effectively, focusing on national security challenges.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The role involves improving Python development workflows, leading projects across teams, mentoring engineers, and enhancing developer productivity using various tools and systems.

The role involves enhancing developer tools for GM's AV engineers, addressing pain points, and mentoring team members to improve productivity and maintain quality code efficiency.

The role involves building awareness of technologies, mentoring talent, promoting a culture of engineering excellence, and collaborating on critical business issues.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Lead technical direction on projects, mentor engineering teams, and build scheduling tools and forecasting interfaces for support agents. Collaborate with product and design teams to convert vague problems into technical solutions.

As a Staff Applied Machine Learning Engineer, you'll design and implement LLM applications, integrating ML features to enhance user experiences and scalable services.

The Staff Full Stack Engineer will enhance machine learning workflows at Cruise by developing UX experiences, backend integrations, and overseeing system architecture and performance metrics.

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