Requirements:

• At least 1 year of hands-on experience in data labeling, annotation, AI training or evaluation, content quality, or a similar operational environment.
• Bachelor’s degree or at least 4 years of relevant professional experience in place of a degree.
• Demonstrated understanding of data quality metrics, annotation processes, and guideline-driven workflows.
• Basic understanding of artificial intelligence and machine learning concepts, particularly the relationship between training data quality and model performance.
• Familiarity with project management and collaboration platforms such as Notion, Axiom, JIRA, Linear, or equivalent tools.
• Previous experience leading or mentoring small teams in data labeling, annotation, content quality, or related operations is highly valued.
• Strong domain expertise in at least one relevant field, such as design, psychology, philosophy, writing, or another humanities discipline, is preferred.
• Proven ability to manage multiple concurrent projects and prioritize effectively in a fast-paced environment.
• Strong experience reviewing domain-specific work, maintaining data quality, and improving operational processes.
• Experience with coaching, performance management, training development, and certification programs is an advantage.
• Strong analytical capabilities and the ability to use data and KPIs to identify trends and drive continuous improvement; SQL knowledge is a plus.
• Experience managing distributed teams is desirable.
• Excellent written and verbal communication skills, with the ability to build rapport, communicate clearly, and align diverse stakeholders.
• Exceptional organizational skills and attention to detail.
• Proactive and structured approach to problem-solving, with a strong focus on continuous improvement.
• Ability to combine strategic thinking with hands-on execution.
• Strong interest in developing high-performing teams and scaling reliable, high-quality Human Data operations.
• Fluent English communication skills.
• Ability to work effectively in a highly collaborative, flat, and fast-moving environment where initiative and ownership are expected.

Benefits:

• Fully remote working opportunity, subject to applicable employment and location requirements.
• Competitive compensation, with international salary details shared during the recruitment process.
• Equity participation as part of the overall rewards package, where applicable.
• Comprehensive medical, dental, and vision coverage for eligible employees, depending on location and employment type.
• Access to retirement benefits such as a 401(k) plan for eligible U.S.-based positions.
• Short- and long-term disability insurance and life insurance for eligible employees.
• Paid sick leave and additional benefits depending on location and jurisdiction.
• Various employee discounts, perks, and additional rewards.
• Opportunity to work at the intersection of AI, human data, and advanced machine learning systems.
• Direct impact on the quality of data used to train and evaluate next-generation AI models.
• Opportunity to lead and develop a high-performing distributed team.
• Hands-on exposure to complex AI training and evaluation operations.
• Fast-paced environment with significant opportunities to contribute ideas, improve processes, and take ownership.
• International and collaborative working environment.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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