Data Architect, Robotics

About the role

At Mind Robotics, we're building generalized physical AI -robotic systems capable of dexterous, adaptive, and reasoning-intensive work in real-world industrial environments. High-quality data is the foundation of everything we do, from training core models to evaluating real-world performance. We're looking for a Data Architect to design and build our data engine - enabling scalable data pipelines, high-quality datasets, and fast iteration across modeling and robotics teams.

Responsibilities

• Design and implement scalable pipelines for collecting, processing, and preparing data for model training
• Partner closely with modeling teams to ensure data is structured for maximum training velocity
• Develop systems for data storage, retrieval, and workflow orchestration
• Manage cloud compute and infrastructure supporting large-scale data processing
• Enable tight feedback loops between data, models, and real-world performance
• Design systems for automated data validation, quality control, and labeling workflows
• Improve consistency, reliability, and scalability of datasets
• Build pipelines and tools for querying, visualizing, and analyzing large datasets
• Continuously improve data pipelines to reduce bottlenecks and latency

Requirements

• Proven experience building scalable data pipelines and infrastructure
• Deep understanding of data processing, storage, and workflow orchestration
• Experience working across the full data lifecycle: ingestion, processing, validation, and dataloading
• Ability to design systems that support both training and evaluation needs
• Experience managing cloud-based data infrastructure and compute workflows
• Familiarity with large-scale data processing systems
• Experience building or scaling data quality, validation, and labeling pipelines
• Strong intuition for what makes high-quality training data
• Experience building tools for data exploration, querying, and visualization
• Strong proficiency in Python programming
• Experience with robotics, multimodal data, or embodied AI systems
• Experience working closely with ML or research teams

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