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← MONEY FORWARD VIETNAM CO.,LTD

AI QA Data Quality Specialist Hybrid QA

MONEY FORWARD VIETNAM CO.,LTD · Hồ Chí Minh
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Type
Full-time
Work mode
On-site
Level
Staff
Industry
IT - Software
Salary
Thương lượng
Location
Not Available, Hồ Chí Minh, Hồ Chí Minh

Overview

  • 7 million B2C users; 140,000+ business customer
  • AI System Quality Assurance
  • Design and execute test strategies for AI/ML-powered applications and features.
  • Validate AI model outputs for accuracy, reliability, and consistency.
  • Perform prompt testing, response evaluation, and edge case validation for AI systems.
  • Identify issues such as hallucinations, bias, incorrect reasoning, or unstable responses
  • Define acceptance criteria and quality benchmarks for AI-driven features.
  • Data Engineering & Data Pipeline Testing
  • Validate data pipelines (ETL/ELT) used to prepare datasets for AI models.
  • Test data ingestion, transformation, and loading processes to ensure reliability.
  • Verify data integrity between source systems, data warehouses, and AI models.
  • Detects and reports data anomalies, schema changes, missing data, or transformation errors.
  • Create data validation rules and automated data quality checks.
  • Dataset & Model Evaluation
  • Validate training datasets and feature engineering pipelines.
  • Monitor dataset quality to prevent data drift or unexpected data changes.
  • Define and track AI model evaluation metrics such as accuracy, precision, recall, and response quality.
  • Collaborate with data scientists to analyze model performance and identify improvement areas.
  • Test Automation
  • Develop automated tests for AI APIs, workflows, and data pipelines.
  • Build automation frameworks to test AI output regression and data validation.
  • Integrate automated testing into CI/CD pipelines.
  • Collaboration & Process Improvement
  • Work closely with AI engineers, data engineers, product managers, and QA teams.
  • Provide feedback during AI model development and deployment cycles.
  • Contribute to building AI testing standards, data quality guidelines, and QA best practices.
  • Your Skills and Experience
  • Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field.
  • 5+ years of experience in software QA, test automation, or data validation and 2+ years of experience in AI & Data quality testing
  • Experience testing APIs, web services, or distributed systems.
  • Strong knowledge of SQL and data validation techniques.
  • Strong with Python for data automation, typescript and or Java for other automation.
  • Understanding of machine learning concepts and AI system behavior.
  • Experience with test automation tools.
  • Experience testing AI systems, LLM applications, or chatbots.
  • Experience with big data platforms.
  • Knowledge of prompt engineering or AI evaluation methods.
  • Experience working with cloud platforms AWS
  • Familiarity with CI/CD and DevOps practices.
  • Generative AI: Enthusiastic user of Generative AI and advanced AI tooling to streamline workflows and significantly accelerate project delivery timelines.

Benefits

Company tripsTraining

Summary of facts from the official posting. View original ↗

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