13 of 13 Permanent Weaviate Jobs in the UK

orchestration AI/ML Engineering Python, PyTorch, TensorFlow, JAX NLP, deep learning, model optimisation Evaluation frameworks and guardrails Data & Platforms Vector databases (Pinecone, Weaviate, FAISS, Milvus) Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow ...

platforms such as Azure ML, AWS SageMaker, Vertex AI, Databricks, Modal, and Fly.io. Deploy and manage vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/PromptOps practices using tools such as: Weights & Biases, MLflow, LangSmith, LangFuse, PromptLayer, Humanloop, Helicone, Arize Phoenix Benchmark, evaluate ...

platforms such as Azure ML, AWS SageMaker, Vertex AI, Databricks, Modal, and Fly.io. Deploy and manage vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/PromptOps practices using tools such as: Weights & Biases, MLflow, LangSmith, LangFuse, PromptLayer, Humanloop, Helicone, Arize Phoenix Benchmark, evaluate ...

Gemini as well as self-hosted LLMs along with MCP integrations Implement Retrieval-Augmented Generation (RAG) techniques leveraging vector databases (Pinecone/ChromaDB/Weaviate/pgvector/etc), search engines such as ElasticSearch/Solr using both TF/IDF BM25 based full text search as well as similarity ...

experience with GenAI platforms: OpenAI, Azure OpenAI, LangChain, or similar frameworks Experience building RAG applications with chunking, vectorisation, retrieval strategies Vector databases: pgvector, Pinecone, Weaviate, or similar DevOps maturity: Infrastructure as Code (Terraform, Bicep, ARM templates), advanced CI/CD Containerisation and orchestration: Docker and Kubernetes (AKS) Database expertise: PostgreSQL ...

architecture, including microservices, event-driven patterns, RAG, Graph RAG, and multi-agent systems.Vector Databases & Embeddings: Experience with embedding models and vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS).Advanced AI Concepts: Complex task decomposition for agents, reasoning engines, knowledge graphs, autonomous agent design, and evaluation methodologies for AI systems.Software Engineering: Strong ...

Gemini . Implement RAG Pipelines Support the design and delivery of Retrieval-Augmented Generation (RAG) solutions using vector databases such as Pinecone or Weaviate . Develop Production-Ready Services Write clean, maintainable code in Python and/or JavaScript , contributing to microservices and APIs that meet performance, security, and reliability ...

fast without compromising on code quality, testing, and operational excellence . Nice to have Experience with tools such as LangChain, LlamaIndex, Haystack, Hugging Face, Weaviate, CrewAI, AutoGen , or similar. Hands-on work with Retrieval Augmented Generation , AI agents, and agent orchestration frameworks. Experience working with unstructured data (documents, conversations, images ...

move fast without compromising on code quality, testing, and operational excellence. Nice to have Experience with tools such as LangChain, LlamaIndex, Haystack, Hugging Face, Weaviate, CrewAI, AutoGen, or similar. Hands-on work with Retrieval Augmented Generation, AI agents, and agent orchestration frameworks. Experience working with unstructured data (documents, conversations, images ...

CrewAI) in production. Strong Python engineering skills with solid testing, optimisation, CI/CD, and code quality; Experience implementing and scaling vector databases (Pinecone, Weaviate, Milvus) for retrieval and reasoning workloads. Deep expertise in cloud‐native AI engineering on AWS, with Azure knowledge and ability to design distributed, fault‐tolerant ...

production Strong Python development skills Hands-on experience with: Prompt engineering and evaluation Retrieval-Augmented Generation (RAG) Embeddings and vector databases (e.g. FAISS, Pinecone, Weaviate, Chroma) Experience building LLM-backed services using FastAPI/Flask or similar Strong understanding of trade-offs around accuracy, latency, cost and scalability Highly Desirable ...

orchestration workflows Designing and maintaining backend services and APIs (primarily Python, FastAPI/Flask) Building and scaling data pipelines and search systems using: ElasticSearch, Weaviate, Pinecone, and other vector databases Engineering secure, containerised architectures using Docker and Kubernetes Ensuring high availability, fault tolerance, and performance for mission-critical workloads Providing ...

cost. Design and run cloud-native AI services across AWS and Databricks, including ingestion and embedding pipelines. Scale and operate vector search infrastructure (Weaviate, OpenSearch, Algolia, AWS Bedrock Knowledge Bases). Implement strong observability, CI/CD, security, and governance across AI workloads. Enable future architectures such as multi-model … large-scale data or embedding pipelines. Proven experience building and operating production AI systems , including RAG pipelines, LLM-backed services, and vector search (Weaviate, OpenSearch, Algolia). Proficiency in Python , with experience deploying containerised services on Kubernetes using Terraform . Solid understanding of distributed systems, cloud architecture, and API design ...