Top Machine Learning Engineer Jobs in Denver & Boulder, CO

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

Lead and develop embedded software solutions for AI-driven safety products, ensuring accuracy of algorithms and guiding technical efforts within the team.

Analyze complex challenges and enhance AI infrastructure through advanced machine learning, while mentoring engineers and developing production-grade systems.

As a Staff Machine Learning Engineer, you'll define technical strategies, design ML models, implement real-time ML pipelines, and deploy systems at scale to enhance Coinbase's operations and user protection.

Lead machine learning initiatives at Vetcove, designing, building, and deploying ML models to improve decision-making in veterinary practices. Collaborate with teams to integrate models and establish best practices, while mentoring peers and enhancing real-world outcomes.

Develop and maintain machine learning infrastructure and platforms, drive MLOps solutions and collaborate with stakeholders for efficient ML services.

As a Staff Machine Learning Engineer at Zocdoc, you will develop and mentor while working on scalable ML models to enhance healthcare search experiences.

Lead the MLOps infrastructure team to build cloud-based analytics, establishing AI/ML strategies, and mentoring staff while focusing on performance metrics.

As a Staff Machine Learning Engineer, you'll enhance and innovate Qualtrics' ML systems, collaborating across teams to optimize AI architectures and ensure scalable solutions, while mentoring juniors.

Lead AI product initiatives on Edge devices, optimize ML models for Edge compute constraints, and develop AI solutions using petabyte-scale data.

The role involves scaling training systems for speech technologies, building internal tools, and innovating data strategies in machine learning.

The Staff Machine Learning Engineer will lead technical strategy, collaborate on product development, ensure operational excellence, and foster team quality and ownership.

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

The Distinguished Machine Learning Engineer will drive modern technology adoption, solve complex business problems, mentor talent, and lead data engineering initiatives.

Develop and maintain machine learning models for production systems, optimize ML pipelines, and ensure efficient data processing and model performance monitoring.

The Staff Machine Learning Engineer will lead AI system development, fine-tune models, and design infrastructure for scalable applications.

Responsible for designing, developing, and deploying ML models to optimize supply chain processes, collaborating with cross-functional teams, and mentoring junior scientists.

The Senior Machine Learning & Computer Vision Engineer role involves developing computer vision models, researching AI methods, working with large datasets, and implementing MLOps best practices to enhance Dandy's 3D dental platform.

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

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 Software Engineer will collaborate with researchers to develop and deploy ML models for pricing, handling model operations and challenges.

Lead AI/ML initiatives to design, develop, and deploy AI solutions. Analyze requirements, build pipelines, and ensure ethical AI practices while mentoring team members.

The Senior Machine Learning Engineer will develop AI agents for healthcare workflows, collaborating with various teams to enhance patient engagement and automate processes using cutting-edge technology.

As a Senior Software Engineer on the ML Platform team, you will build and optimize software applications for machine learning training, automate processes, and support model deployment.

Design and build hybrid retrieval systems, develop pipelines for operational knowledge, and architect knowledge graphs while collaborating with experts.