Top Senior Machine Learning Jobs

Lead the development and deployment of AI and machine learning models, mentor junior data scientists, and collaborate with cross-functional teams to align solutions with business goals.

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

The Machine Learning Engineer will develop and optimize large-scale ML models, build low-latency inference pipelines, and collaborate with teams to enhance performance and automate ML processes.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

Research and apply advanced machine learning techniques to solve autonomy system problems, providing leadership and deploying solutions in real-world environments.

The Senior Engineer in Machine Learning will develop algorithms using machine learning techniques on biomedical datasets, prototype solutions, and collaborate with teams to ensure data quality and performance measures.

Responsible for designing, building, and maintaining machine learning models in production, collaborating with cross-functional teams and ensuring best practices in ML engineering.

The Senior AI Scientist will develop innovative machine learning techniques for MRI, coordinating with teams and enhancing product capabilities through advanced model development and software maintenance.

Develop machine learning models for search ranking and personalization at Faire, leveraging data to help local retailers thrive.

Lead a team of ML engineers in building complex personalization systems, improve model quality, and mentor engineers while coding hands-on.

Lead a team of ML engineers to build and improve personalization systems. The role involves hands-on coding and technical leadership.

Lead a team of ML engineers to build personalized systems while mentoring others and ensuring technical excellence. Focus on architecture and collaboration with product and engineering teams.

Lead a team of ML engineers to build complex personalization and optimization systems, balancing hands-on coding with technical leadership.

Lead a team of ML engineers to build personalized systems while mentoring peers and collaborating with product and engineering teams. Take part in model development and define the technical roadmap.

Lead a team of ML engineers to build personalization systems, improve model quality, and establish best practices while balancing technical work and team leadership.

Lead a team of ML engineers in building advanced personalization systems, managing technical roadmaps, mentoring engineers, and collaborating with cross-functional teams.

Lead a team of ML engineers to build personalization systems by architecting complex algorithms, mentoring, and collaborating with cross-functional teams.

Lead a team of ML engineers in developing personalization systems, balancing hands-on coding with technical leadership and collaboration across teams.

Lead and mentor a team of ML engineers in developing advanced personalization systems, focusing on system architecture and model quality improvements.

Lead a team of ML engineers to develop personalization systems. Responsibilities include team leadership, system architecture, and contributing to model development.

Lead a team of ML engineers to develop advanced personalization and optimization systems while mentoring, managing technical projects, and collaborating across departments.

Lead a team of ML engineers to build personalization systems, architect complex models, and drive improvements in model quality while mentoring the team.

Lead a team of ML engineers to build and enhance personalization systems, balancing technical contributions with team leadership, and improving system quality and reliability.

Lead a team of ML engineers to build advanced personalization systems, balancing technical work with leadership, mentorship, and collaboration across teams.

Lead a team of ML engineers to build personalization systems, architect complex ML infrastructures, and drive improvements in model quality and system reliability.