• Pioneer Cutting-Edge Technology: Introduce and implement cutting-edge ML technologies, integrating them into our products and processes to enable the future of health monitoring • End-to-End Ownership: Own design and operation of robust ML infrastructure – building scalable data, model, and deployment pipelines that ensure reliable delivery of models to production. • Cross-functional Collaboration: Partner with R&D, firmware, data, and backend teams to ensure ML inference operates reliably and scales to Pods everywhere. • Optimize for Performance: Drive cost-effective, scalable, and high-performance ML systems by optimizing compute, storage, and deployment resources across training and inference • Enhance Tooling and Platforms: Develop tooling, micro services, and frameworks to streamline data processing, experimentation, and deployment • Effective Remote Communication: Thrive in a remote work environment, ensuring clear and direct communication.