Remote: Lead AI Data Quality & Labeling Team

OpenKrill; United States; Remote; USD 104,000 - 170,000; Full time

Benefits offered by this job

401(k) retirement plan

Medical, vision, and dental coverage

Job summary

SpaceXSI is seeking a hands‑on leader to guide a team of AI Tutors responsible for delivering high‑quality training data and evaluations that power SpaceXSI models. You will set data quality standards, review domain work, and drive process improvements while executing labeling tasks and collaborating with Human Data Managers, engineers, and senior leaders.

The role emphasizes coaching, performance reviews, and building scalable operations across remote and in‑office environments, with a focus on

Qualifications

• 1+ years of hands‑on experience in data labeling, annotation, AI training/evaluation, content quality, or similar operational domains.
• Professional experience building scalable, high‑performance technology applications.
• Demonstrated experience with data quality metrics, annotation processes, and guideline‑driven workflows.
• Basic understanding of AI and machine learning concepts and how high‑quality training data impacts model performance.
• Experience with performance management, coaching, training program development, and certification frameworks.

Responsibilities

• Own end‑to‑end quality and delivery for assigned Human Data projects.
• Lead, coach, and performance‑manage a team of AI Tutors.
• Oversee labeling and reviewing tasks to maintain high standards.
• Ensure strict guideline adherence, taxonomy management, and quality assurance processes.
• Drive efficiency by identifying bottlenecks and implementing process improvements.
• Build, update, and deliver training materials and benchmark tasks.

Skills

Data labeling

Team leadership

Quality assurance

Performance management

AI basics

Tools

SQL

Job description

SpaceXSI is seeking a hands‑on leader to guide a team of AI Tutors responsible for delivering high‑quality training data and evaluations that power SpaceXSI models. You will set data quality standards, review domain work, and drive process improvements while executing labeling tasks and collaborating with Human Data Managers, engineers, and senior leaders.

The role emphasizes coaching, performance reviews, and building scalable operations across remote and in‑office environments, with a focus on