Senior Machine Learning Engineer (Consumer Team), Hyderabad
Warner Bros. Discovery
- Location
- Hyderabad - Phoenix Equinox Tower 2
- Work model
- On-Site
- Level
- Senior
- Posted
- 13h ago
Skills
About this role
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. Senior Machine Learning Engineer (Consumer Team), Hyderabad About Warner Bros. Discovery: Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com . Meet our Team Warner Bros. Discovery (WBD) brings together iconic entertainment, news, and sports brands including HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, and Food Network. Within the SPARK organization, our Hyderabad Machine Learning Engineering team turns first-party audience signals into ML capabilities for identity, audience intelligence, advertising, personalization, forecasting, engagement, and retention. At WBD, MLEs do rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure — feature stores, training and serving pipelines, and MLOps — that makes our work reliable, repeatable, and scalable. We build primarily on Databricks , with strong working knowledge of Snowflake and AWS , and we are an early, enthusiastic adopter of agentic AI development workflows.
About the Role
Warner Bros. Discovery (WBD) brings together iconic entertainment, news, and sports brands including HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, and Food Network. Within the SPARK organization, our Hyderabad Machine Learning Engineering team turns first-party audience signals into ML capabilities for identity, audience intelligence, advertising, personalization, forecasting, engagement, and retention. At WBD, MLEs do rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure — feature stores, training and serving pipelines, and MLOps — that makes our work reliable, repeatable, and scalable. We build primarily on Databricks , with strong working knowledge of Snowflake and AWS , and we are an early, enthusiastic adopter of agentic AI development workflows. What You’ll Do Technical Leadership & Architecture Design and operate low latency online serving systems for fraud scoring, message decisioning and real-time personalization Build ML models for identity resolution, audience intelligence, content affinity modeling, genre-preference modeling and time-series forecasting across global markets Integrate with personalization systems to consume in-app user signals Design feature pipelines that fuse real-time streaming signals with batch-computed features for online scoring Partner with Product, Engineering, and Data Science to translate business problems into well-scoped ML solutions Evaluate new technologies and approaches, including DCR-native modeling, graph ML, agentic ML orchestration, and LLM-augmented pipelines, with clear build/buy/partner recommendations. Production ML