Senior Data Scientist - Video AI team, Bangalore at Warner Bros. Entertainment Inc.

, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

25 Apr, 26

Salary

0.0

Posted On

25 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Video AI, Model Deployment, Data Pipelines, Computer Vision, Collaboration, Experiment Tracking, Model Versioning, Distributed Computing, Telemetry, Real-Time Inference, Agile Development, PyTorch, JAX, HITL Workflows, Model Evaluation

Industry

Entertainment Providers

Description

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 Data Scientist - (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 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: 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. 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: 5+ years of experience in Applied science, with end-to-end ML workflow expertise Strong background in model retraining, fine-tuning, and evaluation techniques Research work and having publications/patents in some conferences. Computer vision experience is a must for Applied Research role Suggest and develop models Experience owning production ML or data services end-to-end (design → deploy → operate) with strong debugging and on-call instincts. Familiarity with modern orchestration and CI/CD for ML, containerized serving, and scalable storage/indexing. Pragmatic approach to telemetry (traces, metrics, logs) and using it to improve quality, latency, and cost. Strong collaboration with ML researchers/engineers and product teams. 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 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 Trains/finetunes video & image models, builds data pipelines, writes clean PyTorch/JAX, adds tests & ablations. Practical experience with training curves, hyperparam search, model distillation/quantization, export to ONNX/TensorRT. Familiar with modern detectors/segmenters (e.g., SAM/Mask2Former/Grounding-DINO, Retina/CenterNet/YOLOv8+), face detection and recognition models, embedding models. What We Offer: A Great Place to work. Equal opportunity employer Fast track growth opportunities 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 www.wbd.com/guiding-principles/ 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, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Responsibilities

The role involves shipping orchestrated pipelines for training and inference, designing reusable services, and managing production workflows at scale. Additionally, the candidate will be responsible for monitoring production models and integrating various workflows into training pipelines.