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Role Summary The AI/ML Tech Lead drives the end-to-end architecture, implementation, and scaling of multimodal AI systems in the media organization. They lead teams delivering media understanding, personalization, search, moderation, and automation. This role ensures engineering excellence, scalability, and robustness in all AI systems. Detailed Responsibilities Architecture & Technical Leadership Architect large-scale multimodal AI systems handling video, audio, and image pipelines. Design scalable training, inference, and data ingestion systems for media AI. Lead design of video AI features such as: o Scene detection o Video summarization o Content moderation o Annotation workflows o Multimodal search and discovery Design and optimize RAG pipelines pulling from transcripts, frames, subtitles, metadata. Execution & Delivery Oversee model development, integration, deployment, and monitoring. Manage cross-functional delivery with engineers, designers, and media teams. Drive sprint planning, architecture reviews, and performance evaluations. Technical Excellence & Governance Enforce best practices in coding, testing, model governance, and documentation. Build and maintain MLOps standards and model lifecycle processes. Ensure secure, compliant handling of media assets and user data. Team Leadership Mentor ML engineers across levels. Lead technical interviews, onboarding, and capability building. Must-Have Skills Expert in CV, NLP, speech models, and multimodal transformer models. Robust understanding of GPU optimization, distributed training (DeepSpeed, Horovod). Experience with real-time/near-real-time video processing. Hands-on with: o MLflow, Ray, Airflow o KServe, Triton Inference Server o Vector DBs, RAG, LangChain Preferred Skills Experience with broadcast/OTT platforms, MAM systems, and DAM workflows. Experience with generative imaging (Secure Diffusion) or video generation. Qualifications 710 years AI/ML experience, including leadership roles. 5 years+ ML engineering experience. Bachelors/Masters in CS/AI. .