To apply for this job, you need to complete both steps below:

STEP 1:

Please click the link to submit your application directly to the company: 

Careers

Your application will only be received by Recruiter if submitted via above link. 

STEP 2:

Kindly scroll to the bottom of this page and complete the short VinUni Tracking Form.

Filling out this form alone does not count as applying. Kindly remind this form is not part of the company’s application process. It only helps Careers, Alumni, Industry and Development (CAID) Department discover more opportunities and follow up in case of system issues.

Key Responsibilities

• Help design and iterate on data quality standards, judgment rules, and acceptance criteria for LLM training and evaluation scenarios;
• Review and adjudicate data outputs against quality standards, identify issues, and close the loop on corrections to ensure accuracy and consistency;
• Dig into complex, ambiguous, and edge cases; drive discussion and turn conclusions into reusable judgment rules and knowledge assets;
• Track quality metrics, root-cause issues, and drive improvements in production processes and execution;
• Partner cross-functionally with production, product, algorithm, and policy teams to align on quality standards and connect the "standard → production → acceptance → feedback" loop.
  
  

Qualifications

Minimum Qualifications

• Currently pursuing an Undergraduate degree in data, statistics, computer science, law, linguistics or social sciences
• Excellent English proficiency (listening, speaking, reading, writing) with accurate comprehension of English video and text content; IELTS 7.5 / TOEFL 105 or equivalent
• Strong logical thinking with structured problem-decomposition, abstraction, and articulation skills; detail-oriented, with your own point of view on "what makes good data."
• Demonstrated ability to interpret and apply complex guidelines or policies in writing-focused workflows, and some experience evaluating qualitative content or using data to improve processes. Internship, research, and project experience all count.
  
  

Preferred Qualifications

• Additional experience with content policy, operational guideline development, or enforcement workflows.
• A self-starter mindset, solution-oriented thinking, and the ability to manage multiple priorities in a fast-paced, collaborative environment.
• Familiarity with machine-executable logic, labeling frameworks, or test-set workflows.
• Experience collaborating with Policy, Product, Governance, Engineering, or Training teams through internships, projects, research, or full-time roles.
• Knowledge of scenario coverage, positive/negative balance, and dataset validation.
• Internship, academic project, campus organization, or experience in data quality, quality assurance, content moderation, compliance, content operations, editorial review, or AI data / annotation is a strong plus;
• Proficient in Excel and common data tools; hands-on experience with mainstream LLM products (ChatGPT, Claude, Gemini, etc.) and a basic understanding of AI capability boundaries preferred;