Top Machine Learning Jobs in Denver & Boulder, CO
Build AI and Machine Learning solutions to transform user experience and workflow efficiency of enterprise services. Collaborate with a team to produce quality software and solutions for enterprise customers worldwide.
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Design and develop systems that support the creation of large scale, big-data driven, machine learning models integrated into our product.
Designing, building, and managing distributed services for Underwriting & Credit at Cash App. Leading cross-team projects, ensuring code quality, collaborating with various teams, and supporting development capabilities through mentoring.
Featured Jobs
Join our team as a Staff Machine Learning Engineer at Workiva. Spearhead the architecture and delivery of cutting-edge machine learning solutions, lead projects, develop tools and systems, and ensure the reliability and support of ML infrastructure. Collaborate with product teams, provide technical leadership, and communicate complex technical issues effectively.
Senior Machine Learning Engineer responsible for developing cutting-edge ML models and algorithms for measurement, providing insights for strategic investment decisions. Partner with various stakeholders to refine growth strategies and inform decisions. Stay updated on the latest advancements in machine learning and data science.
Leading a team of engineers to build Dropbox's AI offering, Dash. Responsible for driving product monetization and revenue generation. Must have expertise in distributed systems and backend infrastructure. Minimum 7 years of software engineering experience with 3+ years in management roles.
Gusto is looking for a Senior Applied AI Scientist to join our AI team and build out our Generative AI capabilities.
As an AI Engineer at VORTO, you will define the frontier of logistics optimization, supply prediction, and demand prediction. This role is roughly 80% software engineering and 20% data science. You will work with Go, TensorFlow, PostgreSQL, and various Google Cloud Platform tools to develop 'the brain' of the platform.
Collaborate with Autonomy and Robotics teams to collect data, build data pipelines, maintain cloud infrastructure, suggest new technologies, and stay updated on data engineering trends.
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