General Application - Data Operations Engineer - Remote

Overview

Labelbox is the data factory for generative AI, providing the highest quality training data for frontier and task-specific models. Labelbox’s comprehensive platform combines on-demand labeling services with the industry-leading data labeling platform. The Boost labeling service is powered by the Alignerr community of highly-educated experts, who span all major languages and a diverse range of advanced subjects. They are available on-demand to rapidly generate new data for supervised fine-tuning, RLHF, and more. Labelbox’s software-first approach delivers unmatched control and transparency into the labeling process, leading to the generation of high-quality, consistent data at scale.

In Short

• Build, deploy, and maintain Python scripts and tools for data annotation.
• Identify bottlenecks in the data labeling pipeline.
• Work with quality assurance to ensure data accuracy.
• Integrate third-party tools with Labelbox.
• Provide technical support to project managers and labelers.
• Set up monitoring tools for data annotation performance.

Requirements

• 2+ years of experience in a Technical role.
• Bachelor’s Degree in Engineering, Computer Science, Data Science, or a technical field.
• Proficiency in Python scripting.
• Proficiency in SQL.
• Experience with Labelbox or similar platforms.
• Strong analytical and problem-solving skills.
• Experience with data pipelines and workflow management.
• Familiarity with cloud platforms like AWS, GCP, or Azure.
• English fluency.

Benefits

• Remote-friendly hybrid model.
• Focus on collaboration and connection within tech hubs.
• Encouragement of asynchronous communication.
• Autonomy and ownership of tasks.