AI Data Operations Lead - Quality & Talent Coach

Neura Market; Northern (KY); Hybrid; USD 104,000 - 170,000; Full time

Benefits offered by this job

Health insurance

401(k) plan

Paid sick leave

Equity

Job summary

SpaceXAI is seeking a hands‑on Senior Team Lead to manage a team of AI Tutors responsible for delivering high‑quality training data and evaluations powering our models. You will set data quality standards, review domain work, and scale operations by refining processes and coordinating with data managers and engineers.

This role combines leadership with hands‑on data labeling, review work, and the ability to translate model needs into actionable labeling strategies.

Qualifications

• 6 months+ hands‑on experience in data labeling, annotation, AI training/evaluation, content quality, or related operations.
• Basic understanding of AI and ML concepts and how high‑quality data impacts model performance.
• Bachelor’s degree in Finance, Accounting, Economics, or related fields or 4+ years applicable experience in lieu of a degree.

Responsibilities

• Own end‑to‑end quality and delivery for assigned Human Data projects, reviewing work for accuracy and guideline adherence.
• Lead, coach, and performance‑manage a team of AI Tutors, including conducting regular reviews and driving improvement.
• Oversee labeling and reviewing tasks to maintain high standards and model best practices.
• Ensure strict guideline adherence, taxonomy management, and quality assurance processes.
• Drive efficiency by identifying bottlenecks and implementing process improvements; track KPI dashboards.

Skills

Data labeling

AI training

Quality assurance

Personnel leadership

Project management

Explicit communication

Education

Bachelor’s degree or 4+ years experience

Tools

SQL

Notion

JIRA

Linear

Job description

SpaceXAI is seeking a hands‑on Senior Team Lead to manage a team of AI Tutors responsible for delivering high‑quality training data and evaluations powering our models. You will set data quality standards, review domain work, and scale operations by refining processes and coordinating with data managers and engineers.

This role combines leadership with hands‑on data labeling, review work, and the ability to translate model needs into actionable labeling strategies.