Data Architect

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. What You’ll Do 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 What We’re Looking For 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 Nice to Have Experience with robotics, multimodal data, or embodied AI systems Experience working closely with ML or research teams #J-18808-Ljbffr