Director of Engineering (Physical AI)

Join Scale AI as the Director of Engineering for Physical AI. In this senior leadership role, you will lead a multi-disciplinary engineering organization and own the execution of the Physical AI Data Engine. You will collaborate closely with Operations and GTM to guide product direction and help solve the data bottleneck that stands between today's robotics research and real-world deployment. You will also drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities.

• Diriger une organisation d'ingénierie multidisciplinaire, en définissant et en mettant en œuvre la vision technique pour l'infrastructure de collecte de données et les systèmes de téléopération.
• Collaborer étroitement avec les opérations et le GTM pour orienter la direction du produit et résoudre les problèmes liés aux données.
• Maintenir l'excellence technique et opérationnelle en comprenant profondément les livrables de l'équipe et en identifiant les normes en déclin.
• This role requires significant ownership in a fast-paced environment and you will motivate internal teams to set the pace for business growth
• Strong operator and communicator to create tight feedback loops between teams, surface problems early, and drive decisions with clarity across technical and executive audiences
• Proven ability to independently navigate, execute effectively amidst ambiguity, and strong attention to detail
• Deep fluency in the ML development lifecycle — training pipelines, data flywheels, and evaluation frameworks as systems you've built and owned
• 8+ years of engineering experience in fast-paced environments, including 4+ years direct people management demonstrated history of recruiting, mentoring, and developing high-performing technical teams through rapid growth and change
• Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field
• Experience leading technical execution for complex hardware-software systems, with deep domain knowledge in Robotics, Autonomous Vehicles, Computer Vision, and/or Machine Learning strongly preferred
• Comfortable leading teams across Python, C++, and TypeScript/Node stacks, distributed systems, cloud infrastructure (AWS, Kubernetes), and workflow orchestration (Temporal, Airflow)
• MS or PhD is a plus, though strong practical experience is equally valued
• Hands-on experience with teleoperation systems (ALOHA, UMI, hand tracking), robotic hardware platforms, or imitation learning
• Background in sensor fusion, SLAM, or 3D data processing
• Experience scaling data collection systems globally