Director of Data Quality, Gen AI

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

• Recruit, train, and mentor a high-performing QA team.

• Foster a culture of excellence, accountability, and continuous learning.

• Design, implement, and optimize QA policies and procedures.

• 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.

• Drive initiatives for process improvements and automation in QA.

• Develop long-term quality strategies aligned with company goals and industry trends.

• Align QA objectives with overall business strategy.

• Work with operations, product, engineering, and client teams to optimize annotation guidelines and processes.

• Represent the QA function in client meetings and strategy sessions. Analyze quality metrics and KPIs to drive decision-making.

• Prepare and present detailed reports to senior management.

• Maintain compliance with industry standards and regulatory requirements. Stay updated on advancements in QA technologies and methodologies.

About You

• Bachelor’s or Master’s degree in Data Science, Computer Science, Quality Management, or a related field.

• Minimum of 5 years in quality management, particularly in data annotation or related industries.

• Proven track record of leading QA teams and scaling processes in fast-paced environments.

• Expert knowledge of QC/QA methods, including consensus scoring, Inter-Rater Reliability (IRR), and statistical process control.

• Familiarity with data annotation tools, machine learning workflows, and statistical analysis software.

• Experience with automation and AI-driven quality assurance tools is a plus.

• Certifications such as Six Sigma Black Belt or ISO Quality Management are highly desirable.

• Exceptional leadership, team-building, and communication skills.

• Strong problem-solving and analytical abilities, with an innovative and data-driven mindset.

• High adaptability and effectiveness in a fast-paced, client-centric environment.

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.