Staff Machine Learning Engineer- Video AI/Computer VisionWarner Bros. Discovery • United States
Staff Machine Learning Engineer- Video AI/Computer Vision
Warner Bros. Discovery
- United States
- United States
Über
Welcome to Warner Bros. Discovery the stuff dreams are made of. 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. About You
We are looking for a passionate machine learning expert to lead design and development of next-gen video intelligence efforts that drive key applications powered by multimodal video understanding. You have significant experience in building reliable machine learning products in the computer vision domain. Furthermore, you are passionate about multi modal learning and how AI can transform the media & entertainment industry and make all the amazing content accessible to everyone around the world. Roles & Responsibilities
Architect, build and scale computer vision and multimodal capabilities to support video understanding use-cases within WBD. Work closely with Principal Engineers on defining technical vision and strategy for the platform, as well as on prioritizing capabilities alongside with Product team. Develop or fine-tune models for fine grained scene segmentation, annotation, summarization, metadata generation, and selection from videos. Use open-source and off-the-shelf gen AI models as the starting point for model fine-tuning and improvements, maximizing precision and recall on WBD content and objectives. Help build a culture of innovation and engineering excellence by providing guidance to a team of machine learning engineers. Collaborate with adjacent engineering teams to ensure tight integrations to production pipelines in media supply chain and video streaming applications. Evaluate and work with vendors to ensure product deliverables and engineering standards are met, when applicable. Be a thought leader and engineering and operational excellence champion. Demonstrate and foster a culture of growth mindset and curiosity for keeping up with the evolving state of the art and be nimble to rapidly adapt to new models and architectures. Mentor, influence engineers across organizations and lead by example with high quality work at the organization level. What to Bring
7+ years of coding experience in the industry (C/C++, Java, Go, Python) 5+ years of applied machine learning experience to CV tasks Masters/PhD degree required Excellent familiarity with state-of-the-art large-language-models, image and video models and their applications to multi modal tasks Ability to implement algorithms from state-of-the-art papers in the domain of computer vision (in particular, video processing) Excellent architecture and design skills applied to Machine Learning products Experience with PyTorch and/or TensorFlow Very strong foundations in Computer Science, Data Structures and Algorithms Ability to transfer high level, abstract and ambiguous tasks into a set of clear technical requirements Ability to understand and embrace complex business interest and operations, and communicate the impact of AI in less technical terms with stakeholders Systematic and pragmatic engineer, balancing business sense of urgency with engineering excellence Ability to assess different solutions for the same problem with key metrics, trade-offs and be able to make an informed decision
Sprachkenntnisse
- English
Hinweis für Nutzer
Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klicken Sie auf „Jetzt Bewerben“, um Ihre Bewerbung direkt auf deren Website einzureichen.