Powering generalist robotics and world models with multi-million-hour annotated egocentric data, hand tracking, upper-body/whole-body motion capture, tactile sensing, and simulation for OpenAI, Google DeepMind, Meta, Figure, 1X, Skild, Genesis AI, and Dyna... Backed by South Park Commons.
About the role
Strategy & Leadership: Develop and execute the global data operations strategy, aligning with company goals and client needs in the robotics/AI ecosystem. End-to-End Process Ownership: Oversee the entire data pipeline: planning collection campaigns, managing annotation workflows, implementing quality control systems, and ensuring timely dataset delivery. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Experience: 10+ years in operations, program management, or data management, with at least 5 years in a leadership role. Direct experience in robotics, AI data, autonomous vehicles, or a related technical field is required
- Proven Track Record: Success in building, scaling, and optimizing complex operational processes in a fast-paced environment
- Leadership: Strong leadership and team management skills, with an ownership mindset to drive projects and targets
- Technical Acumen: Ability to understand technical requirements for robotics data (sensors, modalities, formats). Experience with data QA tools, basic scripting (Python), or project management software is a strong plus
- Communication: Excellent verbal and written communication skills, with the ability to manage stakeholders at all levels
More about this role
As the Global Director of Data Operations, you will own the entire data operations lifecycle across multiple regions. You will build and lead scalable processes for high-quality, multimodal robotics data collection, annotation, and delivery. Your leadership will ensure our global clients receive training-ready datasets that power the next generation of intelligent robots.
Strategy & Leadership: Develop and execute the global data operations strategy, aligning with company goals and client needs in the robotics/AI ecosystem.
End-to-End Process Ownership: Oversee the entire data pipeline: planning collection campaigns, managing annotation workflows, implementing quality control systems, and ensuring timely dataset delivery.
Team & Vendor Management: Build and lead a hybrid team of internal specialists and external vendors. Set performance metrics, conduct reviews, and foster a culture of quality and efficiency.
Quality & Scale: Design and implement systems to scale operations while maintaining stringent data quality standards for model training. Establish key performance indicators (KPIs) for throughput, accuracy, and cost.
Cross-functional Collaboration: Act as the primary...
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