Senior Machine Learning Engineer at Warner Bros. Entertainment Inc.

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

24 Apr, 26

Salary

245700.0

Posted On

24 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning Engineering, Model Retraining, Fine-Tuning, Evaluation Techniques, Open-Source Model Servers, Distributed Computing, Experiment Tracking, Model Versioning, NLP, Reinforcement Learning, Real-Time Inference Systems, Streaming Data Pipelines, Agile Development, Collaboration

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. 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 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, 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. 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. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $132,300.00 - $245,700.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation. If you’re a qualified candidate with an arrest or conviction record, please know that your application will be considered in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Responsibilities

The role involves building and maintaining pipelines for model fine-tuning and retraining, as well as integrating and maintaining vector search services. The engineer will also design scalable model serving solutions and monitor production models for performance.