Warner Bros. Discovery - Senior Machine Learning Engineer - Video AI

Description : Who We Are :

When we say, the stuff dreams are made of, were not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth.

Behind WBDs 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 whats 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 (Video AI), Bangalore.

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 Medias premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses.

Meet Our Team :

At Warner Bros. Discovery, we are reimagining how machine learning transforms storytelling.

As part of the AI / ML organization, focusing on supporting applications of AI to video, the Machine Learning Engineer Services group powers infrastructure and backend services behind production workflows.

We're looking for an experienced ML Engineer with strong fundamentals and infrastructure experience to help build reusable components and services for video understanding, video summary, and video classifications.

You will be part of a team focused on re-training, model hosting, cost optimization, and managing production workflows at scale.

Roles & Responsibilities :

• Ship orchestrated pipelines for training, batch / stream inference, and evaluation with lineage, versioning, and observability.
• Design, build, and operate reusable services for training, batch / online inference, and vector / lexical search that meet clear SLOs.
• Build / own vector + lexical search stacks and indexes; manage ingestion, filters, caching, and re-ranking.
• Create reliable data / feature and evaluation pipelines with strong lineage, versioning, and observability.
• Implement model deployment / rollout patterns (canary / AB, shadow) with monitoring and fast rollback.
• Drive cost, reliability, and performance improvements across GPU / CPU workloads.
• Integrate and maintain vector search services and semantic similarity infrastructure.
• Design scalable model serving solutions for open-source and foundation models.
• Develop systems for experiment tracking, model versioning, and evaluation.
• Monitor production models for drift and performance degradation.
• Manage compute cost and resource optimization across distributed training jobs.
• Integrate Human-in-the-Loop (HITL) workflows and offline labeling into training pipelines.
• Support model deployment for varied model architectures, including Vision-Language Models, Convolutional Neural Nets, and Embedding Generation models.
• Stand up and maintain Feature Store and data versioning infrastructure.
• Architect and implement RAG pipelines for video metadata, summarization, and Q&A.
• Build evaluation frameworks to assess LLM performance, hallucination frequency, and structured response accuracy.

What to Bring :

What We Offer :

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.

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.

(ref : hirist.tech)