Job Description
Job Title: AI/ML Engineer Senior Associate LevelExperience: 5+ yearsIndustry: Media Preferred Role SummaryThe Senior Associate AI/ML Engineer builds production-grade ML and multimodal systems that support media workflows such as automated metadata extraction, video understanding, speech transcription, moderation, and recommendation. They own model development, MLOps integration, and production deployment while mentoring junior engineers. Detailed ResponsibilitiesModel & Pipeline Development Build and deploy multimodal ML models spanning NLP, CV, ASR, OCR, and video analytics. Develop robust pipelines for:o Video frame extraction, shot detectiono Speech-to-text, speaker diarizationo Image tagging, content moderationo Multimodal embeddings (CLIP, SigLIP, VideoCLIP) Implement RAG (Retrieval Augmented Generation) with multimodal indexing.Optimization & Performance Engineering Optimize model latency for real-time content tagging or streaming workflows. Implement batching, quantization, distillation, or GPU optimizations.MLOps and Deployment Build CI/CD pipelines for ML using GitHub Actions, Jenkins, or Azure DevOps. Deploy models as microservices using Docker, Kubernetes, KServe, or FastAPI. Integrate observability tools (Prometheus, Grafana) for model monitoring.Media Engineering Integration Integrate AI into CMS platforms, OTT apps, media asset management (MAM) systems. Create APIs for search, recommendations, auto-captioning, and content summaries.Collaboration & Mentorship Collaborate with product, content, and media engineering teams. Mentor associate engineers and review code. Must-Have Skills Strong Python + PyTorch/TensorFlow. Experience with NLP, CV, speech models. Knowledge of multimodal LLM frameworks (LangChain, LLaVA, LlamaIndex). Strong understanding of vector search (Pinecone, Weaviate, FAISS). Hands-on with Kubernetes, Docker, CI/CD. Preferred Skills Experience with Whisper, BLIP, ViT, SAM, and video transformers. Experience with cloud ML stacks: SageMaker, Vertex AI, Azure ML.
