We are looking for a Senior / Lead QA Engineer with hands-on experience in end-to-end testing of AI/ML-powered and cloud-based media platforms.
The ideal candidate is not only technically proficient but also AI-aware in their QA approach informed on the latest AI test strategies, conversant with AI-powered tools for test case generation and execution, and comfortable experimenting with new AI-enabled frameworks that enhance automation efficiency.
You will help set up intelligent QA systems integrated into CI/CD pipelines, driving test automation and turnaround time (TAT) efficiencies across the team.
Key Responsibilities:
- Own QA strategy, planning, and execution for AI/ML applications and microservices within the CLEAR AI platform.
- Design, automate, and optimize test cases across functional, integration, regression, and performance testing.
- Validate AI/ML model outputs for accuracy, consistency, and bias; collaborate with data scientists to fine-tune test strategies for non-deterministic systems.
- Stay informed on AI-driven testing approaches and tools; apply them to enhance test coverage and reduce manual effort.
- Experiment with and onboard AI-enabled testing frameworks that support CI/CD-linked automation and continuous validation.
- Build and maintain intelligent test automation systems that improve overall system efficiency and TAT.
- Test end-to-end content workflows involving video, audio, and text transcoding, speech-to-text, computer vision, content QC, and metadata enrichment.
- Develop and maintain automated test frameworks using tools like Playwright, PyTest, Selenium, Postman, JMeter, or Robot Framework.
- Integrate QA seamlessly into CI/CD pipelines (Jenkins, GitHub Actions, or similar).
- Collaborate closely with engineering, DevOps, and product teams to reproduce and resolve defects efficiently.
- Contribute to improving QA standards, documentation, and test data management practices.
- Support performance benchmarking, scalability, and regression testing of AI-enabled workflows.
Required Skills & Experience:
- 610 years of QA experience in product development or enterprise platform environments.
- Strong understanding of SDLC, STLC, Agile methodologies, and defect lifecycle.
- Proven experience in API testing, automation, and performance testing of distributed or cloud-based systems.
- Familiarity with AI test strategies and exposure to AI/ML testing tools (for model validation, dataset evaluation, or automated test generation).
- Comfort with exploring and integrating new AI-driven frameworks to accelerate QA automation.
- Familiarity with media domain concepts (audio/video codecs, subtitles, speech-to-text, NLP, or computer vision) preferred.
- Working knowledge of databases (SQL/NoSQL), scripting (Python preferred), and test automation frameworks.
- Experience with cloud platforms (AWS / Azure / GCP) and CI/CD pipelines.
- Strong analytical, documentation, and debugging skills.
- Excellent communication and collaboration skills across cross-functional teams.
Nice to Have:
- Prior experience with Media Supply Chain, Broadcast, OTT, or Post-production workflows.
- Familiarity with M&E platforms.
- Basic understanding of AI metrics (precision, recall, accuracy) and statistical validation of model outputs.
Education:
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
