QA Engineer AI/ML

Welcome to Warner Bros. Discovery… the stuff dreams are made of.

Who We Are…

When we say, "the stuff dreams are made of," we're not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD's vast portfolio of iconic content and beloved brands, are the
storytellers
bringing our characters to life, the
creators
bringing them to your living rooms and the
dreamers
creating what's next…

From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.

Your New Role
:

Join one of the world's largest and most innovative Media & Entertainment companies as a
QA Engineer - AI/ML

, where

you'll

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,

you'll

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.

1. 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.

2. 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.

3. 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.

4. 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.

5. 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:

• Bachelor's or

Master's 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.

How We Get Things Done…

This last bit is probably the most important Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at

along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.

Championing Inclusion at WBD

Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law.

If you're a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our
accessibility page
for instructions to submit your request.