Senior AI/ML Model Tester

1 week ago

Gurgaon, Haryana, India beBeeQuality Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Job Opportunity

A seasoned professional in AI/ML testing is required to ensure the quality, fairness, and reliability of AI/ML models and systems. The ideal candidate will have strong knowledge of machine learning concepts, model validation, and bias testing.

Key Responsibilities:

  • Develop 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.
  • Design and implement 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.
  • Evaluate compliance with AI governance, security, and quality standards.
  • Prepare detailed test reports, dashboards, and documentation for stakeholders.
  • Participate in CI/CD pipelines for continuous model testing and deployment.
  • Analyze and resolve defects, anomalies, and performance bottlenecks in ML-driven applications.

Requirements:

  • At least 2+ years of experience in AI/ML testing or a related field.
  • 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.

Preferred Qualifications:

  • 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.

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