Lead AI & Deep Learning Engineer

We are seeking a Lead AI & Deep Learning Engineer to connect classic ML/deep learning with agentic AI patterns for real-time live-stream workflows. You will deliver production-ready agentic systems for content scanning, tagging, audio/visual classification, and contextual ad insertion, while designing event-driven microservices over WebSockets with vector search/OpenSearch and Weights & Biases evaluation. Responsibilities Design and deploy advanced agentic AI frameworks, including context management, MCP over WebSockets, and event-driven architectures for autonomous enterprise workflows Build and fine-tune traditional ML and deep learning models for classification, OCR (Optical Character Recognition), and audio spectrogram analysis Architect and optimize high-performance search and retrieval systems using OpenSearch / Elasticsearch and vector databases Implement rigorous evaluation pipelines in Weights & Biases (or equivalent ML/LLMOps tools) to validate new model versions against evals before production switching Collaborate in a fast-paced, experimental Kanban setup with daily discussions, technical reviews, and rapid prototyping Deliver robust autonomous agentic workflows over WebSockets that handle content scanning and live streaming tagging without hallucinations Integrate high-accuracy classification, OCR, and audio processing models into production MURAL and MURAL LIVE pipelines Maintain comprehensive evaluation and observability dashboards in Weights & Biases governing model updates and agentic tool calls Requirements Proven track record with 5+ years of software engineering experience spanning traditional machine learning/deep learning (classification, OCR, computer vision/audio) and modern agentic AI workflows Demonstrated experience building stateful, event-driven microservices and agentic frameworks (MCP, WebSockets, tool-call orchestration) Hands-on experience with search and vector database infrastructure (OpenSearch / Elasticsearch) Strong experience with model evaluation, tracking, and experimentation tools (Weights & Biases) High proficiency in Python & FastAPI backend development Deep understanding of agentic AI frameworks such as LangChain, LlamaIndex, or custom agents English proficiency at B2 level or higher Nice to have Experience with fine-tuning, distillation, and quantization of open-source models Domain background in media & entertainment (broadcast video supply chain, Peacock / live streaming architecture) Familiarity with Go / gRPC microservices Knowledge of Terraform & AWS Cloud infrastructure