Quality Assurance Engineer

3 days ago

Gurgaon, Haryana, India CodeZio Full time

Job Title : QA Engineer (AI/ML)

Location : Gurgaon / Pune

Experience : 4 7 Years

Job Type : Full-time

Notice Period: 30 Days

About the Role :

We are looking for a skilled QA Engineer (AI/ML) to ensure the quality, fairness, and reliability of AI/ML models and systems. The ideal candidate will have strong expertise in testing machine learning pipelines, validating data quality, identifying model biases, and ensuring end-to-end system robustness.

Key Responsibilities :

- Design and execute test strategies for AI/ML models, covering functional, regression, performance, and reliability testing.

- Validate data pipelines and ensure data quality, completeness, and integrity before and after model training.

- Perform bias, fairness, and ethical AI testing to identify potential risks in ML models.

- Develop test frameworks, automation scripts, and tools for ML/AI model validation.

- Collaborate with data scientists, ML engineers, and product teams to define acceptance criteria and test cases.

- Monitor and validate model outputs for accuracy, drift, bias, and anomalies.

- Ensure compliance with AI governance, security, and quality standards.

- Create detailed test reports, dashboards, and documentation for stakeholders.

- Participate in CI/CD pipelines for continuous model testing and deployment.

- Investigate and resolve defects, anomalies, and performance bottlenecks in ML-driven applications.

Required Skills & Qualifications :

- 47 years of experience in Quality Assurance / Testing, with at least 2+ years in AI/ML testing.

- Strong knowledge of machine learning concepts, model validation, and bias testing.

- Hands-on experience with Python, PyTest, TensorFlow/PyTorch testing utilities.

- Proficiency in test automation frameworks and scripting.

- Experience with data quality testing tools and validation techniques.

- Familiarity with ML lifecycle tools (MLflow, Kubeflow, SageMaker, or similar).

- Understanding of model fairness, ethics, and responsible AI frameworks.

- Strong analytical, debugging, and problem-solving skills.

- Excellent communication and collaboration abilities.

Good to Have :

- Exposure to Big Data testing (Spark, Hadoop).

- Knowledge of MLOps pipelines and cloud platforms (AWS, Azure, GCP).

- Experience with performance benchmarking of ML models.

- Certification in AI/ML, Testing, or QA automation.

(ref:hirist.tech)

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