Warner Bros. Discovery
Digital News
MachineLearningEngineerII
“Machine Learning Engineer II at Warner Bros. Discovery. Skills: Machine Learning, Python, Production ML systems, Deployment. Build and deploy ML systems. Power personalization, search, recommendations, content understanding”
What You'll Achieve.
Measurable product impact; Meet reliability, scalability, and performance standards
Industry & Context.
What They're Looking For.
Must Have
Graduate degree (MS or PhD) in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field, 2+ years of professional experience building and deploying machine learning systems in production environments, Python programming skills, experience with machine learning frameworks (e. g. , scikit-learn or similar), Experience across the full ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, and deployment, Solid understanding of software engineering best practices, including version control, testing, and CI/CD, Ability to collaborate effectively with cross-functional partners, communication skills, with the ability to explain technical concepts to non-technical stakeholders
Nice to Have
Experience working on large-scale consumer internet products (e. g. , social, streaming, e-commerce, media), Hands-on experience with recommendation systems, search, NLP, or information retrieval, Familiarity with data pipelines, feature stores, or embedding infrastructure, Experience with experimentation platforms, A testing, and experimentation analysis, Knowledge of cloud platforms (AWS, GCP, or Azure), containerization tools (Docker, Kubernetes), Interest in generative AI applications, Interest in the media and news industry
What You'll Do.
Build and deploy ML systems
Power personalization
content understanding
Work on production ML systems
Collaborate with cross-functional teams
Develop and maintain production ML pipelines
Implement rigorous experimentation frameworks
Optimize ML systems for performance
Partner with platform teams
Contribute to code reviews
Contribute to documentation
Contribute to team knowledge sharing
How You'll Work.
Team & Collaboration
Collaborate with cross-functional teams of engineers, data scientists, product managers, and editorial staff; Collaborate effectively with cross-functional partners; Partner with platform and infrastructure teams
Communication Scope
Communication skills; Explain technical concepts to non-technical stakeholders
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