Role Overview
ImpactQA is hiring a mid-level AI Tester / AI Quality Assurance Engineer. This is a full-time role in IN. Part of ImpactQA's Qa hiring. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job Description
As a Test Engineer for AI/ML models and applications, your role will involve designing and executing test strategies to ensure the quality and reliability of AI systems. Your key responsibilities will include:
- Designing and executing test strategies for AI/ML models, data pipelines, and AI-enabled applications
- Validating data quality, data drift, feature integrity, and training/validation datasets
- Testing model accuracy, precision, recall, bias, fairness, and explainability
- Performing functional, integration, regression, and non-functional testing for AI systems
- Automating AI testing using Python, test frameworks, and MLOps pipelines
- Monitoring model performance post-deployment and identifying degradation or drift
- Validating AI outputs against business rules and real-world scenarios
- Collaborating with data scientists, ML engineers, and product teams
- Ensuring compliance with AI governance, privacy, and regulatory standards
- Documenting test cases, test results, risks, and quality metrics
To excel in this role, you should have the following skills and qualifications:
- Strong understanding of Software Testing and QA processes
- Knowledge of Machine Learning concepts (supervised/unsupervised learning, NLP, CV basics)
- Experience with Python and data analysis libraries (Pandas, NumPy, Scikit-learn)
- Familiarity with AI testing techniques: bias testing, adversarial testing, model validation
- Experience with automation tools and CI/CD pipelines
- Understanding of data validation, data drift, and model monitoring
- Knowledge of API testing and cloud platforms (AWS, Azure, GCP) is a plus
- Strong analytical, problem-solving, and communication skills
Preferred experience includes:
- Experience with MLOps tools
- Exposure to Responsible AI, explainability tools, and ethical AI practices
- Experience testing GenAI systems (LLMs, chatbots, prompt validation, hallucination checks)
This is a great opportunity for individuals with a background in B.E/B.Tech., M.C.A., or Graduate (IITs/NITs and BITS graduates preferred) to contribute to cutting-edge AI technology. If you are passionate about testing AI/ML models and applications, we encourage you to apply now. As a Test Engineer for AI/ML models and applications, your role will involve designing and executing test strategies to ensure the quality and reliability of AI systems. Your key responsibilities will include:
- Designing and executing test strategies for AI/ML models, data pipelines, and AI-enabled applications
- Validating data quality, data drift, feature integrity, and training/validation datasets
- Testing model accuracy, precision, recall, bias, fairness, and explainability
- Performing functional, integration, regression, and non-functional testing for AI systems
- Automating AI testing using Python, test frameworks, and MLOps pipelines
- Monitoring model performance post-deployment and identifying degradation or drift
- Validating AI outputs against business rules and real-world scenarios
- Collaborating with data scientists, ML engineers, and product teams
- Ensuring compliance with AI governance, privacy, and regulatory standards
- Documenting test cases, test results, risks, and quality metrics
To excel in this role, you should have the following skills and qualifications:
- Strong understanding of Software Testing and QA processes
- Knowledge of Machine Learning concepts (supervised/unsupervised learning, NLP, CV basics)
- Experience with Python and data analysis libraries (Pandas, NumPy, Scikit-learn)
- Familiarity with AI testing techniques: bias testing, adversarial testing, model validation
- Experience with automation tools and CI/CD pipelines
- Understanding of data validation, data drift, and model monitoring
- Knowledge of API testing and cloud platforms (AWS, Azure, GCP) is a plus
- Strong analytical, problem-solving, and communication skills
Preferred experience includes:
- Experience with MLOps tools
- Exposure to Responsible AI, explainability tools, and ethical AI practices
- Experience testing GenAI systems (LLMs, chatbots, prompt validation, hallucination checks)
This is a great opportunity for individuals with a background in B.E/B.Tech., M.C.A., or Graduate (IITs/NITs and BITS graduates preferred) to contribute to cutting-edge AI technology. If you are passionate about testing AI/ML models and applications, we encourage you to apply now.
Frequently Asked Questions
How do I apply for the AI Tester / AI Quality Assurance Engineer position at ImpactQA?
Use the Apply button above to submit your application directly to ImpactQA. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the AI Tester / AI Quality Assurance Engineer position at ImpactQA located?
This position is based in IN. ImpactQA has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a AI Tester / AI Quality Assurance Engineer at ImpactQA earn?
ImpactQA has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the AI Tester / AI Quality Assurance Engineer role at ImpactQA posted?
This role was posted on May 2, 2026 (51 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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