Top Remote Senior Level Machine Learning Engineer Jobs in CO

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

Design and implement AI capabilities, transition prototypes to production, build agent workflows, optimize data retrieval, and automate evaluation processes.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

The Machine Learning Researcher will design datasets and evaluate environments for agentic systems, focusing on data quality and benchmarking model performance in RL settings. They will collaborate with teams to translate workflows into evaluative frameworks and improve the understanding of high-quality datasets.

As a Lead Machine Learning Engineer at Root, you'll build scalable ML systems, partner with data scientists, and improve operational practices for customer lifetime value modeling.

Lead a team of machine learning engineers and data scientists to develop and deploy styling algorithms for personalized shopping experiences. Champion AI and ML initiatives, collaborate with stakeholders, and oversee the entire algorithm development process.

Lead retention and churn efforts by building survival and lifecycle-state models, classifying churn reasons, creating personalized win-back and next-best-action interventions, optimizing offers/promos, designing uplift experiments, and owning production model lifecycle, monitoring, and MLOps across Product, CRM, Marketing, and Engineering.