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