AI QA & Data Quality Specialist

Tóm tắt công việc
We are seeking an AI QA & Data Quality Specialist to ensure the quality, reliability, and performance of AI-driven products and the data pipelines that support them. This role focuses on validating AI model outputs, testing AI-powered features, and ensuring the integrity and quality of datasets and data pipelines used for training and inference.
You will work closely with engineering, data engineering, and product teams to improve the overall quality of AI systems through systematic testing, data validation, and automation.
Key Responsibilities
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.
Caring Mental & Physical Recreation:
Hybrid working
Full salary in probation & 13th month salary
Social insurance on full salary from probation
Premium Health insurance from probation
Flexible start 8AM-9AM from Mon-Fri
16 days off annually + 1 Birthday Leave
Paternity leave extra 5 days
Annual company trip; Quarterly team building activities
Club activities
Annual health check
Caring Career & Development:
Clear Career path
Foreign language & International technology-related certifications sponsoring
Well-equipped facility: Macbook pro, additional monitor,..
Soft skill workshops
Tech seminars
Monthly and biannually Recognition Awards
Performance review twice/year