The 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 Responsibilities Model 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 detection o Speech-to-text, speaker diarization o Image tagging, content moderation o 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
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
Qualifications 35 years+ ML engineering experience
Bachelors/Masters in CS/AI
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data ScientistEmployement Type: Full time