11 of 11 Remote/Hybrid Weaviate Jobs in the UK

curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to the development ...

with LLM APIs or open source models such as Llama or Mistral Experience building RAG systems with vector databases such as FAISS, Pinecone or Weaviate Ability to evaluate and improve prompts and retrieval quality using clear metrics Understanding of safety practices such as PII redaction and content filtering Exposure ...

with LLM APIs or open source models such as Llama or Mistral Experience building RAG systems with vector databases such as FAISS, Pinecone or Weaviate Ability to evaluate and improve prompts and retrieval quality using clear metrics Understanding of safety practices such as PII redaction and content filtering Exposure ...

with LLM APIs or open source models such as Llama or Mistral Experience building RAG systems with vector databases such as FAISS, Pinecone or Weaviate Ability to evaluate and improve prompts and retrieval quality using clear metrics Understanding of safety practices such as PII redaction and content filtering Exposure ...

Research, MLOps, Data Pipelines, Prompt Engineering, Model Fine-Tuning, Cloud Computing, AWS, Azure, Google Cloud, AI Infrastructure, Transformers, Reinforcement Learning, Vector Databases, Pinecone, Weaviate, Semantic Search, API Development, AI Deployment, Model Serving, AI Automation, Early Stage Startup, AI Startups, Tech Startup, Machine Intelligence, Applied AI, AI Applications, AI Innovation ...

clearly. Eligible for DV security clearance; no sponsorship provided. Desirable: Advanced LLM techniques: agents, tool use, and agentic workflows. Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications. Experience with feature stores (Feast, AWS Feature Store). Containerisation (Docker) and orchestration (Kubernetes, ECS). Infrastructure as Code (Terraform, CloudFormation ...

agent frameworks. Skilled in prompt engineering , integrating foundation model APIs, and LLM fine-tuning techniques. Expertise in building RAG systems , vector databases (e.g., Pinecone, Weaviate), and embedding pipelines. Experience with ML/LLMOps for monitoring, evaluation, and traceability. Solid understanding of distributed systems , microservices, and real-time data processing. Comfortable ...

agent frameworks. Skilled in prompt engineering , integrating foundation model APIs, and LLM fine-tuning techniques. Expertise in building RAG systems , vector databases (e.g., Pinecone, Weaviate), and embedding pipelines. Experience with ML/LLMOps for monitoring, evaluation, and traceability. Solid understanding of distributed systems , microservices, and real-time data processing. Comfortable ...

agent frameworks. Skilled in prompt engineering , integrating foundation model APIs, and LLM fine-tuning techniques. Expertise in building RAG systems , vector databases (e.g., Pinecone, Weaviate), and embedding pipelines. Experience with ML/LLMOps for monitoring, evaluation, and traceability. Solid understanding of distributed systems , microservices, and real-time data processing. Comfortable ...

AI Engineer Generative AI | Global Manufacturing Enterprise Hired by 167 Solutions on behalf of a Global Manufacturing Business Location: UK (Hybrid or Remote Options) (must be UK based) Salary: £60,000 to £100,000 per ...

APIs (OpenAI, Anthropic, Cohere) and open-source AI frameworks (LangChain, LlamaIndex, LangGraph) into production Design and optimise RAG pipelines using embeddings, vector databases (Pinecone, Weaviate, FAISS) and other retrieval systems Work with knowledge graphs and structured data to add richer context and smarter reasoning to AI workflows Develop agentic/… practical, product-focused AI integration Experience building semantic search, RAG pipelines or similar retrieval-heavy AI systems Hands-on with vector databases (Pinecone, Weaviate, FAISS or similar) and large, complex datasets Familiarity with LLM tooling (e.g. LangChain, LlamaIndex) and agentic AI concepts Comfortable in modern backend stacks (Node.js, Python ...