AI Data Ops Lead — Vision & Video

Jobgether SRL; Danmark; Remote; SEK 1,039,000 - 1,558,000; Full time

Benefits offered by this job

Equity opportunities

Medical, vision, dental coverage

401(k) retirement plan (US-based)

Disability insurance

Paid sick leave

Job summary

Jobgether SRL, listing on behalf of a partner company, seeks a Team Lead, Human Data Operations – Vision, Image & Video in Sweden. You will lead a team of AI Tutors responsible for labeling, reviewing, and evaluating visual data across image and video domains.

The role combines people leadership with hands-on data review and quality assurance, driving process improvements and collaborating with data, engineering, and operations teams to translate model requirements into labeling strategies.

Qualifications

• Hands-on experience in data labeling, annotation, AI training or evaluation.
• Experience with data quality metrics and guideline-driven processes.
• Familiarity with project management and collaboration tools.
• Understanding of AI/ML concepts and training data importance.
• Experience leading small teams in data labeling or QA is preferred.

Responsibilities

• Own end-to-end quality and delivery for data projects.
• Lead and coach a team of AI Tutors with performance reviews.
• Participate in labeling and review activities to maintain quality.
• Manage guideline adherence, taxonomy, and QA workflows.
• Identify bottlenecks and implement efficiency improvements.
• Track performance with KPIs and dashboards.
• Develop training materials and certification benchmarks.

Skills

Data labeling

Quality assurance

Team leadership

Project management

Metrics & KPIs

SQL knowledge

Communication skills

Education

Bachelor’s degree or 4 years experience

Tools

Notion

Axiom

JIRA

Linear

Job description

Jobgether SRL, listing on behalf of a partner company, seeks a Team Lead, Human Data Operations – Vision, Image & Video in Sweden. You will lead a team of AI Tutors responsible for labeling, reviewing, and evaluating visual data across image and video domains.

The role combines people leadership with hands-on data review and quality assurance, driving process improvements and collaborating with data, engineering, and operations teams to translate model requirements into labeling strategies.