Note: The job is a remote job and is open to candidates in USA. Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. They are looking for an early leader to help build a new AI business focused on embodied AI, overseeing product development, customer engagement, data operations, and team building.

Responsibilities

• Win the first customers. Lead customer discovery and close initial pilots with humanoid robotics companies, AI labs, and physical AI companies. You’ll engage directly with VPs of AI, Heads of Data, and technical leaders to understand their training requirements and translate those needs into products Stord can deliver
• Define and build the product. Own the data product roadmap across quality tiers—from RGB egocentric video to depth-enhanced and full multimodal datasets with hand pose, annotations, and other metadata. You’ll prioritize what gets built based on customer demand and willingness to pay, while setting and maintaining a high bar for data quality
• Build and run the capture operation. Stand up the warehouse-based data capture program, including camera and rig selection, participant enrollment, edge processing, data pipelines, and dataset packaging. You’ll coordinate across warehouse operations, engineering, and customers to deliver datasets on spec and on schedule
• Build the team. Hire and lead a small, highly senior team, scaling it as the business grows. You’ll set the technical direction and quality bar, make architecture and tradeoff decisions, and ensure the team builds the right systems. You don’t need to write every line of code—you need to know what good looks like and make sure it gets built

Skills

• End-to-end data operations experience. You've built or operated a data operation or data product within robotics, AI, or a related technical environment. You understand the full lifecycle—from defining what data to collect and deploying capture hardware, through annotation and quality control, to delivering production-ready datasets to ML teams
• Technical depth with strong execution. You're technical enough to lead engineers and make sound architecture decisions, but your greatest strength is getting complex initiatives across the finish line. You can evaluate a pipeline design, understand computer vision and ML data formats, and communicate credibly with both engineers and customers. You don't need to be the person writing the pipeline—you need to ensure the right pipeline gets built
• Commercial instinct. You've either sold data products to robotics or AI companies, or you've been the ML customer buying data and understand what makes a dataset genuinely valuable. You can lead discovery, translate customer requirements into a product specification, and carry an opportunity from first conversation through pilot and close
• Exceptional operating range. You're comfortable moving between strategy and execution—negotiating pilot terms in the morning, reviewing an annotation quality report at noon, and briefing a warehouse GM on a deployment that afternoon. You thrive at the intersection of product, commercial, operations, and engineering
• Deep understanding of physical AI. You understand the physical AI landscape, the needs of humanoid robotics companies and AI labs, and the role that high-quality real-world data plays in training vision-language-action models and deploying robots in production. You understand why egocentric demonstration data is one of the critical bottlenecks to scaling embodied intelligence

Company Overview

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