AI Data Quality & Engineering Lead

TaskUs is a provider of outsourced digital services and next-generation customer experience. The AI Data Quality & Engineering Lead will be responsible for architecting and upholding high-quality annotation workflows for AI models. The role involves leading a team of Data Quality Analysts, developing quality assurance processes, and driving transparency and insight.

Requirements

• Bachelor's degree in a technical field (e.g. Computer Science, Data Science) or equivalent professional experience.
• 3+ years of experience in data quality management, data operations, or related roles within AI/ML or data annotation environments.
• Proven track record in designing and executing quality assurance strategies for large-scale, multi-modal data annotation projects.
• Proven track record in a leadership role managing and developing high-performing, remote or distributed teams.
• Deep understanding of data annotation processes, quality assurance methodologies, and statistical quality metrics (e.g., F1 score, inter-annotator agreement).
• Strong data-analysis skills, with the ability to interrogate large datasets, perform statistical analyses, and translate findings into actionable recommendations.
• Excellent communication skills, with experience presenting complex data and quality insights to technical and non-technical stakeholders.
• Proficiency with annotation and QA tools (e.g., Labelbox, Dataloop, LabelStudio).
• High-level of proficiency in common data-analysis tools, such as Excel and Google Sheets.
• Familiarity with programmatic data analysis techniques (e.g. Python, SQL).
• Familiarity with the core concepts of AI/ML pipelines, including data preparation, model training, and evaluation.

Benefits

• Competitive industry salaries
• Comprehensive benefits packages
• Inclusive environment and positive impact on the community
• Internal mobility and professional growth at all stages of an employee's career within TaskUs