Data Collection Lead

Since its founding in 2015, 1X has been at the forefront of developing advanced humanoid robots designed for household use. Our mission is to create an abundant supply of labor via safe, intelligent humanoids. We strive for excellence in all we do, solving some of the hardest problems in robotics with the world’s most talented individuals. Every part of our robots is designed and produced in-house—from motor coils to AI—reflecting our vertically integrated approach. At 1X, you’ll own real projects, be recognized for your achievements, and rewarded based on merit.

As we scale from research and development to full-scale manufacturing, we are looking for a Data Collection Lead to lead a large-scale operation for gathering, labeling, and validating the data that fuels our cutting-edge robotics technology. This role oversees the planning and execution of large-scale data collection operations, ensuring the data is of the highest quality and diversity. This includes managing data collected through Virtual Reality (VR) and other input methods, as well as overseeing the processes for data labeling and validation. The role requires an individual with proven experience in running people-intensive operations at scale, combined with an understanding of technology. Additionally, this role will ensure that operators are prepared to provide exceptional service to customers once Neo robots are deployed in homes.

RESPONSIBILITIES

• Design and lead large-scale data collection operations, ensuring data diversity, quality, and relevance for training and validating robotics systems.

• Manage data collection using VR and other input methods, driving operational efficiency and innovation in data capture techniques.

• Oversee data labeling and validation workflows, ensuring accuracy and consistency across all datasets.

• Build and manage a large, distributed team of operators, providing training, resources, and support to maintain high performance.

• Develop and enforce standards for data quality, ensuring collected data meets stringent criteria for machine learning and robotics applications.

• Plan and scale operations to meet the growing data requirements of the organization, balancing resources, timelines, and output quality.

• Collaborate with engineering and AI teams to align data collection and labeling operations with technical needs and research objectives.

• Establish robust feedback loops to continuously improve data collection processes based on insights from engineering and validation teams.

• Develop metrics to measure the success of data collection, labeling, and validation efforts, using these insights to optimize processes.

• Prepare and transition the operator workforce to support end-customer services as Neo robots are deployed, ensuring seamless service delivery.

• Leverage technology to automate and enhance workflows, reducing manual effort and increasing the scalability of data collection and labeling operations.

Design and lead large-scale data collection operations, ensuring data diversity, quality, and relevance for training and validating robotics systems.

Manage data collection using VR and other input methods, driving operational efficiency and innovation in data capture techniques.

Oversee data labeling and validation workflows, ensuring accuracy and consistency across all datasets.

Build and manage a large, distributed team of operators, providing training, resources, and support to maintain high performance.

Develop and enforce standards for data quality, ensuring collected data meets stringent criteria for machine learning and robotics applications.

Plan and scale operations to meet the growing data requirements of the organization, balancing resources, timelines, and output quality.

Collaborate with engineering and AI teams to align data collection and labeling operations with technical needs and research objectives.

Establish robust feedback loops to continuously improve data collection processes based on insights from engineering and validation teams.

Develop metrics to measure the success of data collection, labeling, and validation efforts, using these insights to optimize processes.

Prepare and transition the operator workforce to support end-customer services as Neo robots are deployed, ensuring seamless service delivery.

Leverage technology to automate and enhance workflows, reducing manual effort and increasing the scalability of data collection and labeling operations.