Top Senior Machine Learning Jobs in Denver & Boulder, CO

Lead training, evaluation, and deployment of ML models for scene understanding and behavior prediction in autonomous vehicles.

You will train, evaluate, and deploy ML models for scene understanding and behavior prediction in autonomous vehicles, while collaborating with engineers.

Develop algorithms in machine learning and statistics to address complex challenges. Design data pipelines and deploy solutions using cloud infrastructure.

As an Associate Technical Architect in Machine Learning, you will design and develop advanced ML models on AWS, ensuring scalability and reliability while collaborating with cross-functional teams.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

Lead and grow the AI/ML Engineering team, manage core AI/ML platform development, ensure production-grade service operational excellence, and develop product strategies.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

Lead a team to develop large-scale data analysis frameworks and ML models for autonomous vehicles, driving project execution and innovation.

The Lead Machine Learning Engineer will design and evaluate models for autonomous driving systems, mentor junior engineers, and utilize large datasets to improve ML capabilities at May Mobility.

As a Senior ML Engineer, you'll build ML infrastructure, ship AI features, define evaluation strategies, and enhance model decision-making in a dynamic startup environment.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.

The Senior Machine Learning Engineer will develop and optimize ML infrastructure, create data pipelines, and model orchestration ensuring data quality and performance monitoring.

The Senior AI/ML Engineer at Cooley will design, build, and maintain enterprise-scale AI/ML solutions across cloud platforms, optimize performance, and collaborate on AI implementations.

The Senior Machine Learning Engineer will develop and deploy machine learning models, mentor teams, and ensure alignment with operational objectives through collaborative data analysis and best practices.

The Staff AI/ML Engineer will develop and prototype AI/ML algorithms, analyze datasets, and mentor team members in an interdisciplinary environment.

This role involves designing, training, and evaluating ML models, collaborating on AI initiatives, and optimizing model performance for practical applications.

The Senior ML Engineer will automate component placement on PCBs, working on R&D and production using ML and optimization techniques.

Lead cutting-edge machine learning research, develop algorithms, and deploy production-ready models in a healthcare-focused AI environment. Collaborate with engineers and clinicians to optimize healthcare systems.

The role involves owning and delivering AI-powered features for Calendly, collaborating with multiple teams, and applying machine learning solutions for product enhancement.

The Senior Machine Learning Engineer will deploy and maintain ML models, collaborate with cross-functional teams, and optimize ML system performance in a fully remote role.

The AI/ML Engineer will develop AI/ML algorithms, analyze multi-domain datasets, and provide training within a research-oriented team.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

As a Senior ML Engineer, you'll own ML-driven features from modeling to deployment, drive innovation in generative AI, and mentor junior members.

The role involves leading ML strategy, architecting systems, designing algorithms, collaborating with teams, and mentoring engineers in AI for enterprise analytics.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.