Top Remote Senior Level Machine Learning Jobs

As a Senior Principal Machine Learning Engineer at Atlassian, you will design and implement innovative machine learning models to enhance products like Jira and Confluence, analyze vast datasets for insights, and collaborate with cross-functional teams to foster AI integration. You'll also mentor colleagues and lead AI knowledge-sharing sessions.

As a Senior Machine Learning Engineer in the Banking team at Cash App, you will develop and maintain machine learning systems to combat fraud in banking products. Your responsibilities will include designing ML pipelines, creating training platforms for models, and applying best practices to enhance ML solutions.

As a Senior Machine Learning Engineer at TrueML, you'll architect and implement ML infrastructure, develop production-grade ML pipelines, and maintain systems for real-time and batch decision-making. You'll collaborate with data engineers and data scientists to scale algorithms and ensure robust deployment of machine learning models.

The Senior Machine Learning Engineer at Samsara will be responsible for developing ML solutions to enhance the safety, efficiency, and sustainability of physical operations. This remote position requires working closely with engineering teams to deliver core infrastructure and services.

As a Principal ML Infrastructure Engineer, you will define and drive the technical vision for Thumbtack's ML infrastructure, lead cross-functional initiatives, architect scalable ML systems, establish engineering standards, mentor teams, and align infrastructure capabilities with business objectives.

The AI/ML Scientist Manager will lead the deployment of AI solutions, ensuring best practices in model operationalization. Responsibilities include framework development, collaborative implementation with Data Scientists, team leadership of ML engineers, managing ML operations with ML Flow, and overseeing CI/CD pipelines.

The Staff Machine Learning Engineer will lead projects within the Square Conversational AI team, focusing on building scalable machine learning solutions. Responsibilities include collaborating with business leaders, developing ML products, mentoring team members, and overseeing the entire ML lifecycle from data collection to production.