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.
Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs.
Your Day to Day
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Recruit, train, and mentor a high-performing QA team.
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Foster a culture of excellence, accountability, and continuous learning.
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Design, implement, and optimize QA policies and procedures.
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Apply advanced QC/QA methods, such as consensus scoring and statistical process control, to ensure quality standards. Identify workflow inefficiencies and implement best practices to enhance efficiency and reduce errors.
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Drive initiatives for process improvements and automation in QA.
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Develop long-term quality strategies aligned with company goals and industry trends.
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Align QA objectives with overall business strategy.
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Work with operations, product, engineering, and client teams to optimize annotation guidelines and processes.
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Represent the QA function in client meetings and strategy sessions. Analyze quality metrics and KPIs to drive decision-making.
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Prepare and present detailed reports to senior management.
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Maintain compliance with industry standards and regulatory requirements. Stay updated on advancements in QA technologies and methodologies.
About You
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Bachelor’s or Master’s degree in Data Science, Computer Science, Quality Management, or a related field.
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Minimum of 5 years in quality management, particularly in data annotation or related industries.
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Proven track record of leading QA teams and scaling processes in fast-paced environments.
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Expert knowledge of QC/QA methods, including consensus scoring, Inter-Rater Reliability (IRR), and statistical process control.
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Familiarity with data annotation tools, machine learning workflows, and statistical analysis software.
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Experience with automation and AI-driven quality assurance tools is a plus.
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Certifications such as Six Sigma Black Belt or ISO Quality Management are highly desirable.
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Exceptional leadership, team-building, and communication skills.
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Strong problem-solving and analytical abilities, with an innovative and data-driven mindset.
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High adaptability and effectiveness in a fast-paced, client-centric environment.
Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.
Annual base salary range
$195,000—$230,000 USD
Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice.
Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.
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