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Senior Machine Learning Engineer- Computer Vision
Senior Machine Learning Engineer- Computer VisionWarnerMedia Services, LLC • CA San Francisco 153 Kearny Street
Senior Machine Learning Engineer- Computer Vision

Senior Machine Learning Engineer- Computer Vision

WarnerMedia Services, LLC • CA San Francisco 153 Kearny Street
12 days ago
Job type
  • Full-time
Job description

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 bringing our characters to life, the bringing them to your living rooms and the 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.

Machine Learning Engineer – Services (Video AI Platform)

Who We Are…

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

Build and maintain pipelines for model fine-tuning and retraining, including LoRA-based workflows and Large Language Models

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

5+ years of experience in machine learning engineering, with end-to-end ML workflow expertise

Strong background in model retraining, fine-tuning, and evaluation techniques

Experience deploying and managing open-source model servers (e.g., Triton, TorchServe, Ray Serve)

Proficient in managing cost-effective distributed computing environments (e.g., Kubernetes, Ray, SageMaker)

Familiar with experiment tracking tools (e.g., MLflow, Weights & Biases) and model versioning strategies

Deep understanding of ML domains including NLP, RecSys, and reinforcement learning

Experience with real-time inference systems and streaming data pipelines is a plus

Familiarity with labeling tools, HITL workflows, and offline data curation strategies

Comfort working in Agile development environments and collaborating across global teams

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. You can find them at along with some insights from the team on what they mean and how they show up in their day to day. 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, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law.

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Senior Machine Learning Engineer Computer Vision • CA San Francisco 153 Kearny Street