Director of Engineering, Physical AI
Scale AI · San Francisco, CA · Physical AI Engineering · listed July 28, 2026
The shape of it
Seniority
Director
Experience asked
4–8 years
Where
Not stated
Stated pay
$302,400 – $378,000 USD
Requirements listed
7
Length
909 words
In the posting’s own words
The Director of Engineering will report to the General Manager of Physical AI, and will be responsible for leading a multi-disciplinary engineering organization. In this senior leadership role, you will own the execution of the Physical AI Data Engine — the platform powering the next generation of Physical AI/Embodied AI. 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.
What it asks for · 7
- 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 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
Also a plus
- 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
What the job covers
- 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
Degree language
- Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field
Tools and skills named
Models & research
- Machine learning5×
- Computer vision
Cloud & infra
- AWS
- Distributed systems
- Kubernetes
Languages
- C++
- Python
- TypeScript
Go to market
- Go-to-market2×
Ways of working
- Cross-functional
- Mentorship
Data
- Airflow
Frameworks
- Node.js
Operations & finance
- Recruiting
Words the posting leans on
- engineering8×
- data7×
- systems6×
- technical6×
- experience5×
- robotics5×
- physical4×
- drive3×
- infrastructure3×
- leading3×
- platform3×
- research3×
- alignment2×
- collaborate2×
- complex2×
- computer2×
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