Data Architect, Robotics

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