MonoSpear Technologies

About the Role :

We are seeking a detail-oriented and innovative AI Test Engineer to join our QA and Machine Learning team.

In this role, you will be responsible for testing AI and machine learning systems, ensuring model accuracy, performance, reliability, and ethical compliance.

You will work closely with data scientists, ML engineers, and software developers to design robust testing frameworks that validate AI-driven applications and ensure they meet business and quality objectives.

This position is ideal for professionals who have a background in software testing, data validation, and AI/ML model evaluation, and who are passionate about ensuring the trustworthiness and fairness of intelligent systems.

Key Responsibilities :

- Design and execute test strategies for AI/ML models, including functional, performance, bias, and robustness testing.

- Evaluate model accuracy, precision, recall, F1-score, and other ML metrics to ensure reliable outcomes.

- Conduct data validation tests to check data integrity, labeling quality, and distribution consistency.

- Test for model drift, overfitting, and generalization issues using statistical and analytical methods.

- Work with data pipelines to verify input preprocessing, feature engineering, and inference accuracy.

- Perform A/B testing, scenario-based testing, and simulation testing for AI models in production.

- Develop automated test frameworks for AI pipelines using tools such as PyTest, Robot Framework, or Selenium.

- Implement continuous testing and integration (CI/CD) processes for ML model deployments.

- Leverage Python, TensorFlow, PyTorch, or scikit-learn to automate and validate ML workflows.

- Integrate test automation into ML Ops pipelines using Azure ML, AWS Sagemaker, or Google Vertex AI.

- Perform stress testing and load testing of AI services (APIs, inference endpoints, etc.

- Validate latency, throughput, and scalability of deployed models.

- Assess ethical and responsible AI practices, ensuring fairness, transparency, and non-bias in predictions.

- Collaborate with data teams to ensure GDPR compliance and data privacy standards.

- Work closely with AI engineers, software developers, and product managers to understand requirements and expected outcomes.

- Contribute to defining test plans, acceptance criteria, and AI model validation documentation.

- Maintain traceability from business requirements to model validation outcomes.

- Document test cases, results, anomalies, and recommendations for improvements.

Required Skills & Qualifications :

years of experience in software testing, QA automation, or data validation.

- Strong experience with Python for scripting and automation.

- Familiarity with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn.

- Solid understanding of data science concepts, model evaluation metrics, and ML lifecycle.

- Hands-on experience with API testing tools (Postman, REST Assured) and automation frameworks (PyTest, Robot Framework, or Selenium).

- Experience with SQL and NoSQL databases for data validation.

- Working knowledge of cloud-based ML platforms (Azure ML, AWS Sagemaker, GCP Vertex AI).

- Experience with CI/CD pipelines, Git, and DevOps practices.

- Strong analytical mindset, problem-solving abilities, and attention to detail.

- Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field