Responsibilities
- Define the long-term technical direction for artificial intelligence and machine learning within the content product landscape.
- Discover and prioritize impactful applications of Generative AI, agent-based systems, and computer vision to enhance content discovery, delivery, and metadata generation.
- Design advanced multimodal machine learning architectures that process and combine visual, auditory, and language-based data.
- Build scalable data infrastructure for machine learning, supporting high-volume data labeling, transformation, and storage across petabytes of content.
- Lead the creation of reusable, cross-functional platform components to replace isolated point solutions with standardized, enterprise-wide systems.
- Assess and apply cutting-edge research in areas such as diffusion models, vision transformers, and multi-agent frameworks.
- Supervise the development of efficient inference pipelines using GPU computing and optimization methods like quantization, pruning, and TensorRT to balance speed and accuracy.
- Establish comprehensive and automated evaluation methodologies using A/B testing, offline and online metrics, and human feedback loops.
- Deploy monitoring systems to track model behavior and pipeline performance, ensuring system stability and operational transparency.
- Act as a technical authority and mentor, guiding data science and ML engineering teams through innovation and best practices.
- Collaborate with senior executives to ensure AI initiatives support overarching business objectives.
