AI Data Quality Lead — Hands-On Team Coach (Remote)

Xai; Palo Alto (CA); Remote; USD 104,000 - 170,000; Full time

Benefits offered by this job

Equity

Medical, Vision & Dental coverage

401(k) retirement plan

Disability insurance

Life insurance

Employee discounts

Job summary

SpaceXAI is seeking a hands-on leader to manage a team of AI Tutors (employees and contractors) responsible for delivering high-quality training data and evaluations. You will set data quality standards, review domain work, and implement scalable processes to improve throughput and accuracy.

The role combines hands-on labeling with operational leadership, driving continuous improvement across labeling strategies and collaboration with Human Data Managers and Engineering.

Qualifications

• Experience with data quality metrics, annotation processes, and guideline-driven workflows.
• Demonstrated experience leading small teams in data labeling, annotation, or related operations.
• Strong communication and stakeholder management skills.
• Proven ability to manage multiple projects and prioritize in a fast-paced environment.

Responsibilities

• Own end-to-end quality and delivery for assigned Human Data projects and review work for accuracy.
• Lead, coach, and performance-manage a team of AI Tutors with regular reviews and action plans.
• Oversee labeling/reviewing tasks to maintain high standards and model best practices.
• Ensure guideline adherence, taxonomy management, and quality assurance processes.
• Drive efficiency by identifying bottlenecks and tracking KPI dashboards.
• Develop training materials, practice tasks, and certification benchmarks.

Skills

Data quality metrics

Team leadership

Coaching

Annotation workflows

Performance management

Data labeling

SQL

Education

Bachelor's degree in Engineering

Master's degree in Engineering

Tools

SQL

Job description

SpaceXAI is seeking a hands-on leader to manage a team of AI Tutors (employees and contractors) responsible for delivering high-quality training data and evaluations. You will set data quality standards, review domain work, and implement scalable processes to improve throughput and accuracy.

The role combines hands-on labeling with operational leadership, driving continuous improvement across labeling strategies and collaboration with Human Data Managers and Engineering.