5 of 5 Contract Weaviate Jobs in the UK excluding London

Server, Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data MLOps & Infrastructure MLOps: Model versioning, monitoring, logging ...

LangSmith or similar Solid NLP background (tokenisation, embeddings, transformers, BERT-style models, sentiment analysis) Experience integrating vector databases (e.g. Azure AI Search, OpenSearch, Pinecone, Weaviate) Cloud experience on Azure, AWS or GCP Familiarity with MLflow, model evaluation frameworks, observability & monitoring Strong understanding of deploying AI systems into real-world production ...

with LangChain, LangGraph, and Indexify , with a deep understanding of RAG architectures . Expert-level SQL and experience with BigQuery and vector databases (Pinecone, Weaviate, Vertex AI Search). Proven track record in MLOps and deploying ML models at scale. Experience moving LLM-based prototypes into production environments with thousands ...

LlamaIndex, Semantic Kernel or similar. Optimize prompt strategies, memory, tools, and policies. RAG & vector search: Architect robust RAG pipelines with vector DBs (Pinecone, Chroma, Weaviate, pgvector), including chunking, hybrid search, embeddings selection, caching, and evaluation. Guardrails & observability: Implement policy/guardrails, safety filters, prompt/content validation, and LLMOps observability … with LLM orchestration frameworks (e.g.,LangChain/LangGraph/LlamaIndex/Semantic Kernel). Proven experience with RAG and vector databases (e.g., Pinecone, Chroma, Weaviate, pgvector). Proficiency in Python (primary) and at least one of JavaScript/TypeScript or Java. Solid foundation in cloud (AWS/GCP/Azure ...

systems with large language models. Build and maintain applications using LangChain to orchestrate complex AI workflows. Implement and manage vector databases (e.g., FAISS, Pinecone, Weaviate, Milvus) for fast similarity search and retrieval. Develop embedding pipelines for unstructured data using models like Sentence Transformers, OpenAI, or Hugging Face. Collaborate with data … with large language models (GPT, BERT, etc.). Fine-tuning and prompt engineering. Experience with vector similarity search. Knowledge of popular vector DBs: Pinecone, Weaviate, FAISS, Vespa, Milvus. Generating and managing embeddings (using models like SentenceTransformers, OpenAI, Hugging Face). Familiarity with LangChain for building LLM-powered applications. Ability ...