Job Summary

AI/ML Test Engineer (AWS/GCP) – Key Responsibilities

• Design and execute test strategies for AI/ML applications and data pipelines.
• Validate machine learning model performance, accuracy, robustness, and reliability.
• Perform functional, integration, regression, API, and end-to-end testing.
• Develop and maintain automated test frameworks using Python and modern testing tools.
• Test AWS-based AI/ML solutions, including SageMaker and Bedrock deployments.
• Verify data quality, model inputs/outputs, and ETL processes.
• Conduct performance, security, and scalability testing.
• Monitor production AI systems for model drift and performance degradation.
• Collaborate closely with Data Scientists, ML Engineers, Developers, and DevOps teams.

Required Skills

• Strong experience in Software Testing and Test Automation.
• Proficiency in Python and SQL.
• Experience with Selenium, Playwright, PyTest, or Robot Framework.
• Good understanding of Machine Learning concepts and model lifecycle.
• Hands-on experience with AWS services such as EC2, S3, Lambda, SageMaker, and CloudWatch.
• Experience in API testing using Postman or REST Assured.
• Understanding of CI/CD pipelines and DevOps practices.

Preferred Skills

• Experience testing Generative AI solutions and Large Language Models (LLMs).
• Knowledge of AWS Bedrock, MLOps, and Responsible AI practices.
• Exposure to performance testing tools and cloud-native testing approaches.
• Familiarity with Agile/Scrum methodologies.

Key Responsibilities

AI/ML Test Engineer (AWS/GCP) – Key Responsibilities

• Design and execute test strategies for AI/ML applications and data pipelines.
• Validate machine learning model performance, accuracy, robustness, and reliability.
• Perform functional, integration, regression, API, and end-to-end testing.
• Develop and maintain automated test frameworks using Python and modern testing tools.
• Test AWS-based AI/ML solutions, including SageMaker and Bedrock deployments.
• Verify data quality, model inputs/outputs, and ETL processes.
• Conduct performance, security, and scalability testing.
• Monitor production AI systems for model drift and performance degradation.
• Collaborate closely with Data Scientists, ML Engineers, Developers, and DevOps teams.

Required Skills

• Strong experience in Software Testing and Test Automation.
• Proficiency in Python and SQL.
• Experience with Selenium, Playwright, PyTest, or Robot Framework.
• Good understanding of Machine Learning concepts and model lifecycle.
• Hands-on experience with AWS services such as EC2, S3, Lambda, SageMaker, and CloudWatch.
• Experience in API testing using Postman or REST Assured.
• Understanding of CI/CD pipelines and DevOps practices.

Preferred Skills

• Experience testing Generative AI solutions and Large Language Models (LLMs).
• Knowledge of AWS Bedrock, MLOps, and Responsible AI practices.
• Exposure to performance testing tools and cloud-native testing approaches.
• Familiarity with Agile/Scrum methodologies.

Skill Requirements

AI/ML Test Engineer (AWS/GCP) – Key Responsibilities

• Design and execute test strategies for AI/ML applications and data pipelines.
• Validate machine learning model performance, accuracy, robustness, and reliability.
• Perform functional, integration, regression, API, and end-to-end testing.
• Develop and maintain automated test frameworks using Python and modern testing tools.
• Test AWS-based AI/ML solutions, including SageMaker and Bedrock deployments.
• Verify data quality, model inputs/outputs, and ETL processes.
• Conduct performance, security, and scalability testing.
• Monitor production AI systems for model drift and performance degradation.
• Collaborate closely with Data Scientists, ML Engineers, Developers, and DevOps teams.

Required Skills

• Strong experience in Software Testing and Test Automation.
• Proficiency in Python and SQL.
• Experience with Selenium, Playwright, PyTest, or Robot Framework.
• Good understanding of Machine Learning concepts and model lifecycle.
• Hands-on experience with AWS services such as EC2, S3, Lambda, SageMaker, and CloudWatch.
• Experience in API testing using Postman or REST Assured.
• Understanding of CI/CD pipelines and DevOps practices.

Preferred Skills

• Experience testing Generative AI solutions and Large Language Models (LLMs).
• Knowledge of AWS Bedrock, MLOps, and Responsible AI practices.
• Exposure to performance testing tools and cloud-native testing approaches.
• Familiarity with Agile/Scrum methodologies.

Other Requirements

AI/ML Test Engineer (AWS/GCP) – Key Responsibilities

• Design and execute test strategies for AI/ML applications and data pipelines.
• Validate machine learning model performance, accuracy, robustness, and reliability.
• Perform functional, integration, regression, API, and end-to-end testing.
• Develop and maintain automated test frameworks using Python and modern testing tools.
• Test AWS-based AI/ML solutions, including SageMaker and Bedrock deployments.
• Verify data quality, model inputs/outputs, and ETL processes.
• Conduct performance, security, and scalability testing.
• Monitor production AI systems for model drift and performance degradation.
• Collaborate closely with Data Scientists, ML Engineers, Developers, and DevOps teams.

Required Skills

• Strong experience in Software Testing and Test Automation.
• Proficiency in Python and SQL.
• Experience with Selenium, Playwright, PyTest, or Robot Framework.
• Good understanding of Machine Learning concepts and model lifecycle.
• Hands-on experience with AWS services such as EC2, S3, Lambda, SageMaker, and CloudWatch.
• Experience in API testing using Postman or REST Assured.
• Understanding of CI/CD pipelines and DevOps practices.

Preferred Skills

• Experience testing Generative AI solutions and Large Language Models (LLMs).
• Knowledge of AWS Bedrock, MLOps, and Responsible AI practices.
• Exposure to performance testing tools and cloud-native testing approaches.
• Familiarity with Agile/Scrum methodologies.