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Persona AI

Robotics Data Pipeline Engineer – Multimodal Data

Pensacola, FL or Houston, TXfulltimemidAdded today

About this role

Develop and maintain robust data pipelines to process multimodal robotic sensor data, enabling AI/ML systems to extract insights from video, audio, and other sensor inputs. The role combines data engineering with robotics domain knowledge to ensure reliable ingestion, transformation, and delivery of high-volume streaming and batch data.

What you'll do

  • Design and build scalable data pipelines for multimodal robotic sensor data (video, audio, IMU, lidar, etc.)
  • Implement data validation, transformation, and quality checks across streaming and batch workflows
  • Optimize data storage, indexing, and retrieval for machine learning model training
  • Monitor pipeline performance, troubleshoot failures, and implement alerting systems
  • Collaborate with robotics, ML, and software engineering teams to understand data requirements
  • Document data schemas, pipeline architecture, and operational procedures

What they're looking for

  • Data pipeline orchestration (Airflow, Kubernetes, or similar)
  • Python, SQL, or similar languages for ETL development
  • Streaming data technologies (Kafka, Spark Streaming, Kinesis)
  • Cloud platforms (AWS, GCP, Azure) or on-premise data infrastructure
  • Data warehousing/lake technologies (Parquet, HDF5, or time-series databases)
  • Version control and CI/CD practices
  • Understanding of robotics sensor data formats and challenges
  • Experience with multimodal or time-series data

Benefits

  • Work on cutting-edge robotics and AI technologies
  • Flexible work location (Pensacola, FL or Houston, TX)
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Persona AI

Persona AI builds humanoid robots and manufactures them at scale. The company is hiring for specialized engineering roles including quality assurance, reinforcement learning, process optimization, robotics software development, and welding to advance their robotics platform.

Website
persona.ai
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Likely interview questions

  • Describe your experience building data pipelines for real-time or streaming data. What challenges did you face and how did you solve them?
  • How would you handle data quality issues when ingesting multimodal sensor data from robots operating in uncontrolled environments?