Description :

Your New Role :

Join one of the worlds largest and most innovative Media & Entertainment companies as a QA Engineer - AI/ML, where youll ensure the quality and reliability of cutting-edge AI and machine learning solutions that are transforming the industry.

Our AI/ML-powered systems play a crucial role in optimizing content production, personalization, and consumer engagement, and your contributions will be instrumental in delivering seamless, scalable, and efficient solutions to our global audience.

As a QA Engineer specializing in AI/ML, youll work closely with data scientists, software engineers, and product teams to rigorously test AI models, data pipelines, and machine learning platforms.

Your role will involve defining and implementing robust quality assurance practices for complex AI systems, ensuring they meet the highest standards of performance, scalability, and security.

If you are passionate about AI, testing, and driving quality excellence in a dynamic environment, this is your opportunity to make an impact.

Quality Assurance for AI/ML Models and Pipelines :

- Develop and execute comprehensive test plans, test cases, and test scripts to validate AI/ML models and data pipelines.

- Perform rigorous testing of machine learning models to ensure accuracy, reliability, and robustness under various scenarios.

- Validate data preprocessing, feature engineering, and model training pipelines for correctness and consistency.

- Identify and address performance bottlenecks in AI systems, ensuring scalability for large datasets and real-time applications.

- Collaborate with data scientists to validate model outputs and metrics against business requirements.

Automation Testing and Tool Development :

- Design and implement automated test frameworks and tools tailored for AI/ML workflows.

- Automate testing of model deployments, APIs, and data pipelines using industry-standard tools and frameworks.

- Create scripts to simulate edge cases, stress conditions, and user interactions for AI systems.

- Build monitoring tools to assess AI model drift, data inconsistencies, and system performance post-deployment.

- Continuously enhance automation coverage and testing efficiency through innovative practices.

Collaboration and Cross-Functional Engagement :

- Work closely with software engineers, data engineers, and product managers to align QA strategies with project goals.

- Participate in code reviews, design discussions, and sprint planning to incorporate QA perspectives early in the development lifecycle.

- Provide actionable feedback and insights to development teams to resolve issues and improve system quality.

- Support end-to-end integration testing of AI/ML solutions across multiple platforms and systems.

- Act as a quality advocate, promoting best practices for testing and validation within the organization.

Governance, Compliance, and Reporting :

- Ensure compliance with data privacy, security, and ethical AI standards during testing and deployment.

- Develop and maintain comprehensive documentation for QA processes, test cases, and system validations.

- Monitor and report on key QA metrics, including defect rates, coverage, and system reliability.

- Support regulatory audits and reviews by providing required testing documentation and evidence.

- Stay up-to-date with industry trends, tools, and practices in QA for AI/ML systems.

Continuous Improvement and Innovation :

- Research and adopt emerging technologies and frameworks for AI/ML testing and validation.

- Drive continuous improvement initiatives to enhance the efficiency and effectiveness of QA processes.

- Proactively identify and resolve quality gaps in AI/ML workflows, ensuring a seamless user experience.

- Contribute to building a culture of quality and accountability within the AI/ML team.

- Mentor junior team members on QA best practices and technical skills.

Qualifications & Experiences :

Academic Qualifications :

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

- Certifications in software testing (e.g., ISTQB, CSTE) or machine learning (e.g., AWS ML, TensorFlow Developer) are a plus.

Professional Experience :

- 3+ years of experience in QA engineering, with at least 1+ years focused on testing AI/ML systems.

- Proven expertise in testing machine learning models, data pipelines, and cloud-based AI solutions.

- Hands-on experience with test automation tools and frameworks such as Selenium, PyTest, JUnit, or similar.

- Familiarity with CI/CD pipelines and tools like Jenkins, GitHub Actions, or Azure DevOps.

- Solid understanding of software testing methodologies, including functional, regression, performance, and stress testing.

Technical Skills:

- Proficiency in Python or Java, with experience in writing test scripts for AI/ML applications.

- Knowledge of AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn.

- Experience with testing tools specific to AI/ML, such as DeepChecks or Alibi.

- Familiarity with data querying languages (SQL) and data processing tools (Pandas, Spark).

- Understanding of cloud platforms (AWS, GCP, Azure) and their AI/ML services.

Other Skills:

- Strong analytical and problem-solving skills, with a detail-oriented approach.

- Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team.

- Passion for quality and a commitment to delivering exceptional results.

- Ability to adapt to a fast-paced and dynamic environment while maintaining a focus on continuous improvement.

- Self-motivated and proactive, with a drive to stay updated on industry trends and best practices