Director of Engineering, Physical AI

Key Responsibilities

• Set and drive the technical vision across data collection infrastructure, teleoperation systems, ML training pipelines, model evaluation frameworks, annotation tooling, and research.
• Lead a multidisciplinary engineering organization—spanning engineering managers, software engineers, ML engineers, and ML research scientists—while designing the organizational structure, talent strategy, and culture required to scale rapidly without compromising on quality or strategic alignment.
• Maintain exceptional technical and operational excellence by deeply understanding team deliverables, asking incisive questions, identifying slipping standards early, and knowing precisely when to step in.
• Drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities.
• Collaborate with researchers and clients to architect and deliver scalable, production-grade data infrastructure tailored for complex robotics workloads.

Required Qualifications

• Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field.
• 8+ years of engineering experience in fast-paced environments, including 4+ years 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, 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 as systems you've built and owned.
• Comfortable leading teams across Python, C++, and TypeScript/Node stacks, distributed systems, cloud infrastructure (AWS, Kubernetes), and workflow orchestration (Temporal, Airflow).
• Proven ability to independently navigate, execute effectively amidst ambiguity, and strong attention to detail.
• Strong operator and communicator to create tight feedback loops between teams, surface problems early, and drive decisions with clarity across technical and executive audiences.

Nice to Have

• 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.

Compensation and Benefits

The base salary range for this full-time position in San Francisco is $302,400–$378,000. Compensation packages include base salary, equity, and benefits. Benefits include comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, generous PTO, and potentially a commuter stipend.