The TMW Center for Early Learning + Public Health (TMW Center) develops, tests, and implements evidence-based interventions designed to promote very young children’s cognitive and social-emotional development, with emerging technologies that enhance—rather than replace—the pivotal role that caregivers play in building healthy young brains. Although there is a rich body of research demonstrating the importance of the early language environment for maximizing early learning, there are very ways to assess the quality of those environments. As a result, when it comes to nurturing their children’s brains, parents often feel like they are in a maze without a map. The TMW Center has launched a wearable device and an accompanying app that uses machine learning to measure and analyze a child’s language environment and provide real-time information as well as personalized feedback and guidance for enhancing that environment. This groundbreaking piece of technology gives parents and caregivers with information they need to engage in robust brain-building interactions — and helps deepen caregiver-child connection. The TMW Center is looking for an ML Validation & Data Operations Manager to lead and monitor operations for continuous algorithm improvement and validation. This will involve guiding the development of data management systems and establishing data assessment strategies to enable efficient and scalable validation processes. The ML Validation & Data Operations Manager will also contribute to defining the vision for current and longer-term algorithm developments. They will collaborate closely with our data science, research, and data management teams to coordinate workstreams, ensure a smooth integration of the developed systems and protocols within broader operations, and align with research developments. This position will report to the CTO, with guidance from the Scientific Director.