14 of 14 Permanent Weaviate Jobs in England

/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS etc.). Experience in architecting and scaling GenAI chatbots Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI) and orchestration tooling (MCP Servers) in More ❯

/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS etc.). Experience in architecting and scaling GenAI chatbots Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI) and orchestration tooling (MCP Servers) in More ❯

/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS etc.). Experience in architecting and scaling GenAI chatbots Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI) and orchestration tooling (MCP Servers) in More ❯

/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS etc.). Experience in architecting and scaling GenAI chatbots Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI) and orchestration tooling (MCP Servers) in More ❯

/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS etc.). Experience in architecting and scaling GenAI chatbots Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI) and orchestration tooling (MCP Servers) in More ❯

first design principles. AI/ML Acumen: Strong foundational knowledge of modern AI concepts, including Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and vector databases (e.g., Qdrant, Pinecone, Weaviate). Data Integration: Hands-on experience designing data pipelines and integrating with diverse enterprise data sources (e.g., relational databases like PostgreSQL, unstructured document stores like SharePoint, APIs, and data warehouses More ❯

Proven hands-on knowledge with: LangChain, AutoGen, LangGraph and RAG Strong proficiency in Python and experience with frameworks like PyTorch or TensorFlow. Experience working with vector databases (e.g., FAISS, Weaviate, Pinecone). Familiarity with HR systems and data (Workday, SAP SuccessFactors, etc.) is a plus. Excellent communication skills and ability to translate technical concepts for non-technical stakeholders. Ideally you More ❯

platform, with a focus on leveraging AI/GAI technologies and large language models (LLMs) Advanced AI Integration : Apply experience with retrieval-augmented generation (RAG), vector databases (e.g. Pinecone, Weaviate, FAISS), and enterprise search for AI-driven knowledge discovery Optimize AI Performance : Utilize practical experience designing structured prompts, fine-tuning models, and cost optimization strategies Cloud Architecture : Incorporate cloud architecture More ❯

mindset, strong communication skills and a team player 5+ years of professional experience in full-stack development. Hands-on experience with RAG systems , vector databases (pgvector/FAISS/Weaviate/ES k-NN), embeddings , and hybrid search (BM25 + vectors). Strong grasp of chunking strategies , metadata, indexing, recall/precision trade-offs, reranking, and evaluation (ground-truth sets More ❯

mindset, strong communication skills and a team player 5+ years of professional experience in full-stack development. Hands-on experience with RAG systems, vector databases (pgvector/FAISS/Weaviate/ES k-NN), embeddings, and hybrid search (BM25 + vectors). Strong grasp of chunking strategies, metadata, indexing, recall/precision trade-offs, reranking, and evaluation (ground-truth sets More ❯

on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient in Python (FastAPI) and React/ More ❯

Active SC Clearance (non-negotiable) - willingness to undergo DV if required - Demonstrable experience deploying open-source LLMs (Llama, Mistral, Falcon) on-premises - Expertise with local vector databases (Chroma, FAISS, Weaviate) in offline deployments - Strong vLLM/Text Generation Inference experience for high-throughput model serving - Proven ability to work on air-gapped systems with no external package repositories - Experience with More ❯

Active SC Clearance (non-negotiable) - willingness to undergo DV if required - Demonstrable experience deploying open-source LLMs (Llama, Mistral, Falcon) on-premises - Expertise with local vector databases (Chroma, FAISS, Weaviate) in offline deployments - Strong vLLM/Text Generation Inference experience for high-throughput model serving - Proven ability to work on air-gapped systems with no external package repositories - Experience with More ❯

WebSockets, media processing, growth experiments Toolkit You’ll Likely Use React, Next.js, Tailwind • React Native/Flutter • Node.js, TypeScript, Firebase/Supabase/Postgres • OpenAI SDKs, LangChain, Pinecone/Weaviate • Vercel/Cloud, CI/CD, Sentry/Crashlytics, Mixpanel/GA This is more than a job, it’s a chance to be a founding builder inside a global More ❯