Mind Robotics

Data Infrastructure Engineer

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. 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

Who can you reach out to