Warner Bros Discovery
Media · Media conglomerate
- HQ
- New York City, US
- Founded
- 2022
- Website
- wbd.com
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.
Warner Bros Discovery currently has 11 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, Principal, System Architecture, Senior Design Technologist, Design Systems, CNN. Most positions are in Engineering.
Warner Bros Discovery's active AI hiring is concentrated in: agents (45%), application (36%), serving infrastructure (18%). 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 (6 roles), United States (4 roles), Poland (1 role).
Job postings at Warner Bros Discovery most frequently mention: Machine Learning, Agentic Systems, Performance Optimization, GCP, Distributed Systems.
In the past 30 days, Warner Bros Discovery has posted 8 new AI-related roles. That is a -33% change versus the prior 30 days (12 → 8).
| Title | Stage | AI score |
|---|---|---|
| Manager, Machine Learning Engineering & Data Science, Hyderabad Manager for a team of Machine Learning Engineers and Data Scientists responsible for building, deploying, and operating large-scale ML systems for consumer platforms, including user behavioral modeling, fraud detection, and transaction intelligence. The role involves leading the development of ML platform capabilities across the full lifecycle (pipeline orchestration, experimentation, deployment, observability) and requires hands-on technical depth in designing experiments, architecting scalable ML solutions, and building production-grade systems. | ServeAgent | 7 |