Richtech Robotics
Robot Data Processing Specialist
As a Robot Data Processing Specialist, you will be responsible for managing the end-to-end lifecycle of data collected from robotic systems from structured collection and parsing, to cleaning, formatting, visualization, and preparing datasets for machine learning and engineering teams. This role requires technical fluency in robot data formats, basic scripting, and a strong focus on data quality and structure. The Day-To-Day Collect and organize multimodal data generated from robot operation sessions (video, IMU, joint state, control inputs, etc.) Parse and process structured robot data using formats such as Protobuf, ROS bags, and URDF Visualize robot movement and sensor data using Foxglove or custom dashboards Perform routine data cleaning, integrity checks, and filtering of corrupted, noisy, or incomplete data Maintain internal dataset structure, metadata consistency, and naming/versioning standards Collaborate with robotics engineers and ML teams to ensure data is usable, labeled, and scalable Contribute to improving data pipelines and internal tooling for automation and visualization The Ideal Candidate You're deeply organized, hands-on, and understand the value of structured, clean data in robotics and AI systems. You've worked with real robot data or simulation logs, and you're comfortable reading URDF files, visualizing sensor data, or scripting to clean and format logs. You might not be a full ML engineer, but you know what high-quality training data looks like and how to build it. Qualifications Familiarity with robotics data structures: URDF, Protobuf, ROS topics/bags Experience with robot data visualization tools such as Foxglove Proficiency in Python or other scripting languages for automation, parsing, and formatting Strong understanding of Linux environments, file systems, and version control Experience working with large data sets in robotics, simulation, or embedded systems Background in Machine Learning or Data Annotation workflows is preferred Bachelor's degree in Computer Science, Robotics, Data Engineering, or a related field
As a Robot Data Processing Specialist, you will be responsible for managing the end-to-end lifecycle of data collected from robotic systems from structured collection and parsing, to cleaning, formatting, visualization, and preparing datasets for machine learning and engineering teams. This role requires technical fluency in robot data formats, basic scripting, and a strong focus on data quality and structure. The Day-To-Day Collect and organize multimodal data generated from robot operation sessions (video, IMU, joint state, control inputs, etc.) Parse and process structured robot data using formats such as Protobuf, ROS bags, and URDF Visualize robot movement and sensor data using Foxglove or custom dashboards Perform routine data cleaning, integrity checks, and filtering of corrupted, noisy, or incomplete data Maintain internal dataset structure, metadata consistency, and naming/versioning standards Collaborate with robotics engineers and ML teams to ensure data is usable, labeled, and scalable Contribute to improving data pipelines and internal tooling for automation and visualization The Ideal Candidate You're deeply organized, hands-on, and understand the value of structured, clean data in robotics and AI systems. You've worked with real robot data or simulation logs, and you're comfortable reading URDF files, visualizing sensor data, or scripting to clean and format logs. You might not be a full ML engineer, but you know what high-quality training data looks like and how to build it. Qualifications Familiarity with robotics data structures: URDF, Protobuf, ROS topics/bags Experience with robot data visualization tools such as Foxglove Proficiency in Python or other scripting languages for automation, parsing, and formatting Strong understanding of Linux environments, file systems, and version control Experience working with large data sets in robotics, simulation, or embedded systems Background in Machine Learning or Data Annotation workflows is preferred Bachelor's degree in Computer Science, Robotics, Data Engineering, or a related field