Machine Learning QA Engineer

Info Resume Edge; Sharjah; On-site; AED 200,000 - 300,000; Full time

Job summary

A tech-driven company is seeking a detail-oriented Machine Learning QA Engineer to ensure the quality and reliability of ML models. You will design and implement test strategies, develop automated testing frameworks, and collaborate with teams for seamless model deployment. The ideal candidate holds a Bachelor's or Master's in a related field and has proven experience in QA for machine learning systems, along with strong skills in software testing practices. This role promises a dynamic work environment focused on innovation.

Qualifications

• Bachelor's/Master's degree in a related field is mandatory.
• Proven experience in QA/testing of machine learning systems required.
• Strong understanding of software testing practices is essential.
• Experience with Python and testing frameworks is necessary.

Responsibilities

• Design and implement test strategies for machine learning pipelines.
• Develop automated testing frameworks for validating ML model inputs.
• Collaborate with teams for seamless model deployment.
• Evaluate data quality throughout the ML lifecycle.

Skills

Quality Assurance

Machine Learning

Automated Testing

Data Validation

Software Testing Practices

Collaboration

Python

Education

Bachelor's/Master's degree in Computer Science, Data Science, or related field

Tools

Python Testing Frameworks (e.g. PyTest, unittest)

ML Frameworks (e.g. TensorFlow, PyTorch, Scikit-learn)

Data Validation Tools (e.g. Great Expectations)

CI/CD Tools (e.g. Git, Jenkins)

Job description

We are seeking a detail-oriented and technically skilled Machine Learning QA Engineer to ensure the quality accuracy and reliability of our ML models and systems. You will work at the intersection of quality assurance and machine learning developing automated and manual test strategies validating data pipelines and verifying ML model performance against business objectives.

Key Responsibilities:

• Design and implement test strategies for machine learning pipelines APIs and models.

• Develop automated testing frameworks for validating ML model inputs outputs and performance.

• Collaborate with ML engineers data scientists and DevOps teams to ensure seamless model deployment.

• Evaluate data quality and integrity throughout the ML lifecycle.

• Test for accuracy bias fairness reproducibility and drift in models.

• Validate and monitor ML models in production environments.

• Write detailed test plans test cases and quality documentation.

• Participate in code reviews and contribute to QA best practices in ML workflows.

Requirements:

• Bachelors/Masters degree in Computer Science Data Science Engineering or related field.

• Proven experience in QA/testing of machine learning systems or data products.

• Strong understanding of software testing practices (unit integration system regression).

• Experience with Python and testing frameworks (e.g. PyTest unittest).

• Familiarity with ML frameworks (e.g. TensorFlow PyTorch Scikit-learn).

• Understanding of data validation tools (e.g. Great Expectations TensorFlow Data Validation).

• Experience testing RESTful APIs and backend systems.

• Familiarity with CI/CD pipelines and version control systems (e.g. Git Jenkins).

Preferred Qualifications:

• Experience with MLOps tools like MLflow Airflow or Kubeflow.

• Exposure to cloud platforms (AWS/GCP/Azure) for model deployment and monitoring.

• Knowledge of model interpretability explainability and ethical AI principles.

• Experience working in Agile/Scrum teams.