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Salary: USD 302,400 - 378,000 / annual
Scale is seeking a Director of Engineering to lead the Physical AI Data Engine organization, a platform powering the next generation of embodied AI and robotics. You will report to the General Manager of Physical AI and own the execution of a multi-disciplinary engineering organization spanning software engineers, ML engineers, and research scientists.
Key responsibilities include setting and driving technical vision across data collection infrastructure, teleoperation systems, ML training pipelines, model evaluation frameworks, annotation tooling, and research initiatives. You will lead and scale a growing engineering organization, designing organizational structure, talent strategy, and culture to support rapid growth without compromising quality or strategic alignment. You'll maintain exceptional technical and operational excellence by deeply understanding team deliverables, identifying slipping standards early, and knowing when to step in directly.
You will drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities. Collaboration with researchers and clients is essential to architect and deliver scalable, production-grade data infrastructure tailored for complex robotics workloads.
Required qualifications include a Bachelor's degree in Engineering, Robotics, Computer Science, or related technical field. You need 8+ years of engineering experience in fast-paced environments, including 4+ years of direct people management with a demonstrated history of recruiting, mentoring, and developing high-performing technical teams through rapid growth and change.
Experience leading technical execution for complex hardware-software systems is essential, with deep domain knowledge in Robotics, Autonomous Vehicles, Computer Vision, and/or Machine Learning strongly preferred. Deep fluency in the ML development lifecycle—training pipelines, data flywheels, and evaluation frameworks—is required, as is comfort leading teams across Python, C++, and TypeScript/Node stacks, distributed systems, cloud infrastructure (AWS, Kubernetes), and workflow orchestration tools (Temporal, Airflow).
You should be comfortable navigating and executing effectively amidst ambiguity with strong attention to detail. Strong operator and communicator skills are essential to create tight feedback loops between teams, surface problems early, and drive decisions with clarity across technical and executive audiences. Travel will be required.
