Top Senior Level Machine Learning Jobs

As a Lead Machine Learning Engineer, you will design, build, and optimize machine learning systems, collaborate with cross-functional teams, and implement best practices for deployment and model governance.

The Lead Machine Learning Engineer will design and implement ML applications, collaborate with teams, optimize models, and ensure performance and governance in machine learning systems.

As an Applied AI ML Senior Associate, you'll solve complex business problems using advanced analytics, develop statistical models, and mentor juniors.

The Senior Machine Learning Engineer will innovate AI features, develop LLM methodologies, perform data preprocessing, and communicate technical concepts. The role requires building and optimizing machine learning models and pipelines.

The Senior / Staff ML Engineer will develop and integrate ML models into production, collaborate across teams, mentor juniors, and shape ML platform strategies.

The Senior Machine Learning Engineer will design and build scalable AI/ML infrastructure, collaborate on model development, and optimize performance in distributed training environments.

Lead model development and automation of analysis processes while designing and testing machine learning algorithms using Python and SQL. Collaborate with teams to provide data-driven solutions and insights.

The Senior Machine Learning Software Engineer will lead the development and optimization of machine learning and computer vision software for edge devices, encompassing the entire software development lifecycle from design to deployment.

The Senior Director will lead teams in developing and evaluating machine learning models, focusing on innovation and collaboration across functions to enhance AI capabilities.

Lead ML model development from conceptualization to deployment, mentor engineers, and influence architectural decisions to enhance Chewy's marketing and product offerings.

As a Senior Machine Learning Engineer, you will design ML APIs, build data pipelines, deploy models, and collaborate with various engineering teams to improve ML solutions for physical operations.