AI Data Operations Lead — Vision & Video

x; California, Northern (MO, KY); Hybrid; USD 104.000 - 156.000; Vollzeit

Zusammenfassung

SpaceXAI seeks a Team Lead for Human Data Operations to guide a small, hands-on team of AI Tutors responsible for training data quality and evaluations powering SpaceXAI models. You will set data quality standards, review domain work, and scale processes while remaining hands-on.

You will coach the team, manage labeling and reviewing tasks, track KPIs, develop training materials, and collaborate with Human Data Managers and Engineering to translate model needs into labeling strategies.

Qualifikationen

• 1+ years hands-on data labeling, AI training/evaluation, or related operations.
• Bachelor’s degree or 4+ years of professional experience in lieu of a degree.
• Experience with data quality metrics and guideline-driven workflows.
• Experience with project management tools such as Notion, Axiom, JIRA, Linear, or equivalent.
• Knowledge of AI/ML concepts and how high-quality data impacts model performance.
• Documented QA experience in creative or media projects.

Aufgaben

• Own end-to-end quality and delivery for assigned Human Data projects, reviewing work for accuracy and consistency.
• Lead, coach, and performance-manage a team of AI Tutors with regular performance reviews.
• Oversee labeling and reviewing tasks to maintain high standards and model best practices.
• Ensure strict guideline adherence, taxonomy management, and QA processes.
• Drive efficiency by identifying bottlenecks and implementing process improvements with KPI tracking.
• Build and deliver training materials, practice tasks, and certification benchmarks.

Kenntnisse

Data labeling

QA metrics

Team leadership

Process improvement

Guideline adherence

Ausbildung

Bachelor’s degree

Tools

Notion

Axiom

JIRA

Linear

SQL

Jobbeschreibung

SpaceXAI seeks a Team Lead for Human Data Operations to guide a small, hands-on team of AI Tutors responsible for training data quality and evaluations powering SpaceXAI models. You will set data quality standards, review domain work, and scale processes while remaining hands-on.

You will coach the team, manage labeling and reviewing tasks, track KPIs, develop training materials, and collaborate with Human Data Managers and Engineering to translate model needs into labeling strategies.