5 of 5 Permanent Faiss Jobs in London

consistent operation. Retrieval‐Augmented Generation (RAG) & Knowledge Architecture – expertise in RAG and knowledge‐grounded systems, including chunking, embeddings, vector databases (Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid search and retrieval evaluation. Familiarity with GraphRAG and agentic RAG. LLMOps, Evaluation & Responsible AI – operationalizing LLM and agentic systems at scale; evaluation harnesses, quality ...

unsupervised ML and AI observability•Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS).•Experience in designing and scaling GenAI chatbots.•Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI) and orchestration tooling ...

technical and non-technical stakeholders.DesirableExperience with workflow automation platforms such as n8n, Power Automate, Dify or similar.Knowledge of vector databases including Pinecone, Weaviate, Chroma, FAISS or Milvus.Experience building Retrieval Augmented Generation (RAG) solutions.Understanding of AI governance, Responsible AI and AI security principles.Exposure to MLOps, model deployment and monitoring frameworks.Experience working ...

delivering complex, cross‐team projects. English — advanced proficiency, written and spoken. Preferred Qualifications Fine‐tuning, RLHF, or model customization. Vector databases (Pinecone, Weaviate, or FAISS) and embedding retrieval. Building agent workflows with MCP servers or modern agent frameworks. Conversational AI and speech (speech‐to‐text/text‐to‐speech ...

teams.• Retrieval-Augmented Generation (RAG) & Knowledge Architecture: Expertise architecting RAG and knowledge-grounded systems—chunking strategies, embeddings, vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid search, reranking, and retrieval evaluation. Familiarity with advanced patterns such as GraphRAG and agentic RAG to maximize factual grounding and minimize hallucination in production. … . Experience with cloud AI platforms (e.g., Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI), vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector, FAISS), containerization and orchestration (Docker, Kubernetes), and distributed computing is advantageous.• Architecture Design: Ability to design end-to-end Generative and Agentic AI architectures that encompass ...