Review and audit labeled datasets for both text and image-based content to ensure accuracy, consistency, and adherence to guidelines
Document and share feedback with the individual labelers
Identify trends and insights in quality performance and mitigate quality performance issues
Communicate quality trends and insights to the customer and calibrate with the customer on instructions and edge cases
Evaluate responses generated by AI for correctness, clarity, relevance, and alignment with task instructions
Apply knowledge of Consumer Packaged Goods domain to accurately classify and/or describe products
Collaborate with cross-functional teams to update labeling workflows and improve quality
Monitor performance metrics (e.g., accuracy rates, inter-rater agreement) and contribute to continuous improvement initiatives
Generate responses with intentional but realistic grammar, spelling, and structural errors
Run calibration sessions to align QA standards across teams and help train new reviewers or analysts
Adapt quickly to evolving guidelines, new task types, and AI model updates in a fast-paced, iterative environment
Ensure that documentation is up to date
Requirements
English as a second language - minimum B2 English proficiency required
C2 level of Japanese
Ability to follow linguistic and situational writing prompts
Excellent written communication and coordination skills
2 years working experience in a corporate/ business environment
Prior experience in at least one: Linguistic QA; Data annotation for NLP/AI projects; ESL/EFL teaching, editing, or copyediting
Keen eye for detail - spotting subtle grammar and structure issues others miss
Comfortable reviewing and providing feedback on structured data
Ability to give actionable and constructive feedback to annotators
Experience with creating and tracking timelines, milestones, and status reports is a plus
Access to your own laptop for work
Preferred: C1 or C2 level English proficiency; Familiarity with error tagging systems; Experience in CPG industry/workflows or retail product knowledge