Top Remote Senior Level Machine Learning Engineer Jobs in CO

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

Lead development of machine learning models for real-time content ranking, translating business objectives into effective ML solutions while managing experiments and data pipelines.

Design and build ML features using LLMs, collaborate on technical architecture, and ensure safety and performance of deployments.

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

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

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

Lead the development of end-to-end machine learning models for search and recommendation systems, collaborating with cross-functional teams at Airbnb.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

The Lead Machine Learning Scientist designs and develops ML solutions, leads project teams, mentors members, and collaborates with clients to solve complex problems.

The Senior Machine Learning Consultant designs and develops machine learning solutions while mentoring team members and collaborating with clients. Responsibilities include conducting R&D on AI/ML models, optimizing model performance, and ensuring adherence to ethical AI practices.