Warner Bros Discovery currently has 12 active AI-related roles in our index. The most common open titles are: MLOps Engineer (AWS), Manager, Machine Learning Engineering & Data Science, Hyderabad, Principal Data Scientist, Senior Design Technologist, Design Systems, CNN, Senior Machine Learning Engineer (Data & Audience Platform Team), Hyderabad. Most positions are in Engineering and Product.
Warner Bros Discovery's active AI hiring is concentrated in: application (42%), agents (42%), serving infrastructure (17%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Warner Bros Discovery is hiring AI talent in: India (7 roles), United States (4 roles), Poland (1 role).
Job postings at Warner Bros Discovery most frequently mention: Machine Learning, Data Governance, Agentic Systems, Data Science, Computer Vision.
In the past 30 days, Warner Bros Discovery has posted 10 new AI-related roles.
Warner Bros Discovery currently has 17 active AI-related job listings. The majority of these roles, specifically 76%, are focused on agents. Engineering is the top function across all these positions. The company is primarily hiring in India, with 14 listings, followed by the United States with 2. Frequent tech tags include agent orchestration, model serving, and guardrails, suggesting a focus on deploying and managing AI agents. In the last 30 days, Warner Bros Discovery has added 13 new AI roles, representing a 160% increase compared to the previous 30-day period.
| Title | Stage | AI score |
|---|---|---|
| Staff Product Manager - Tech - AI/ML Staff Product Manager, Technical (PM-T) for Content Intelligence at Warner Bros. Discovery, focusing on AI/ML capabilities for content localization workflows. This role involves defining requirements, driving execution of AI-powered systems for transcription, subtitling, translation, and dubbing, and leveraging content context to improve quality and consistency. Collaboration with engineering, AI/ML teams, and various stakeholders is key to operationalizing these systems and ensuring successful delivery of localized content across global markets. | AgentData | 7 |