Lead Machine Learning Engineer - ML Infrastructure

Who we are Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale. Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term. About the role: Samsara is the industry leader in AI for physical operations. We're hiring a Lead Machine Learning Infrastructure Engineer to serve as the technical anchor for ML infrastructure across Samsara's Safety AI organization. You will own the architecture and evolution of our end-to-end ML platform — spanning training, experimentation, inference, and edge deployment across more than 2M deployed devices — and be the connective tissue between applied ML teams, security, and data platform. This role is not an execution role sitting under a technical lead; you are the technical lead. Your decisions shape platform direction, unblock multiple product teams, and translate directly into real-world safety outcomes for the industries that run our world. We are open to calibrating this role at Staff, Senior Staff, or Principal level depending on the candidate's scope of experience — what matters most is end-to-end platform ownership and the ability t