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Stord is seeking a Director of Embodied AI to build a new business line from the ground up, leveraging the company's unique position as the largest independent e-commerce fulfillment network in the US (20+ fulfillment centers, 4,000+ warehouse associates, ~100M packages annually). This is a founder-like opportunity to transform Stord's operational footprint into a valuable source of training data for physical AI and robotics.
You will report directly to Stord's CTO and Co-Founder and own the entire Embodied AI business line, including product strategy, customer development, data capture operations, team building, and revenue generation. This is a builder-operator role requiring fluidity between strategy and execution.
Key responsibilities include: (1) Lead customer discovery and establish early partnerships with humanoid robotics companies, AI labs, and physical AI organizations; build relationships with VPs of AI and technical leaders to understand training data needs; own pilot programs and initial revenue generation. (2) Define the data product roadmap—determine what data to collect, how to package it, and where to invest based on customer demand; develop offerings across quality tiers (RGB egocentric video, multimodal datasets with depth, hand pose, annotations, sensor modalities); establish quality standards for next-generation AI models. (3) Design and operationalize warehouse-based data capture programs, including hardware selection, camera rigs, deployment processes, edge processing, and dataset pipelines; partner across operations and engineering to ensure reliable collection and delivery. (4) Hire and lead a senior technical team as the business scales; set technical vision, architecture principles, and operating model; make critical engineering and product tradeoffs.
You bring deep experience building AI data products or operations for robotics, AI, or ML companies. You understand the full lifecycle of AI data—from collection requirements and capture system deployment to annotation, quality management, and delivery to ML teams. You have built processes and infrastructure enabling high-quality datasets at scale. You possess technical depth across data infrastructure, ML systems, and robotics, with the ability to evaluate technical decisions and drive execution without necessarily writing every line of code.
