51 to 73 of 73 Pinecone Jobs in England

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

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

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

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

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

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

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

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

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

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

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

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

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

systems: chunking strategies, document schemas, metadata, hybrid/dense retrieval, re-ranking, and grounding. Manage vector/keyword indexes (e.g., Azure AI Search, pgvector, Pinecone/Weaviate). Develop and deploy advanced NLP, information retrieval, and recommendation systems that enhance Chambers and Partners’ research and product offerings, including document understanding ...

deployment. ML/LLM Engineering Work with AI+ML pipelines throughAzure ML,AWS SageMaker,Vertex AI,Databricks, orModal/Fly.iofor lightweight LLM deployment. Utilizevector databases(Pinecone, Weaviate, Milvus, ChromaDB, pgVector) and embedding stores. UseAI-powered dev tools(GitHub Copilot, Cursor, Codeium, Aider, Windsurf) to accelerate iteration. ImplementLLMOps/PromptOpsusing: Weights & Biases … LlamaIndex and the broader GenAI ecosystem. Deep understanding of LLM behavior, prompt optimization, embeddings, retrieval and data preparation workflows. Experience with vector DBs (FAISS, Pinecone, Milvus, Weaviate, ChromaDB). Hands-on knowledge of Linux, Bash/Powershell, containers and cloud environments. Strong communication skills, creativity and a systems-thinking mindset. ...

GenAI in production, such as: Fine-tuning or integrating transformer models Building RAG pipelines and semantic search Working with vector databases (e.g., Pinecone, Weaviate, Milvus, OpenSearch, etc.) Self-motivated and proactive, able to work independently where needed while contributing to team outcomes. Passion for clean, efficient, maintainable code ...

GenAI in production, such as: Fine-tuning or integrating transformer models Building RAG pipelines and semantic search Working with vector databases (e.g., Pinecone, Weaviate, Milvus, OpenSearch, etc.) Self-motivated and proactive, able to work independently where needed while contributing to team outcomes. Passion for clean, efficient, maintainable code ...

engineering skills, including chain-of-thought reasoning RAG & Knowledge Systems Implementation of Retrieval-Augmented Generation (RAG) pipelines Experience with vector databases such as CockroachDB, Pinecone, or similar Embedding model optimisation and semantic search Context window management and chunking strategies MCP & Tool Integration Model Context Protocol (MCP) implementation LLM tool calling ...

engineering skills, including chain-of-thought reasoning RAG & Knowledge Systems Implementation of Retrieval-Augmented Generation (RAG) pipelines Experience with vector databases such as CockroachDB, Pinecone, or similar Embedding model optimisation and semantic search Context window management and chunking strategies MCP & Tool Integration Model Context Protocol (MCP) implementation LLM tool calling ...

engineering and chaining logic for AI-based tasks. Background in backend engineering (Python, NodeJS, or similar). Familiarity with tools like LangChain, OpenAI API, Pinecone, or similar . A problem-solver mindset—focused on delivering tangible outcomes using AI. Comfortable working in a fast-paced, agile environment. Excellent communication ...

researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, Hugging Face, OpenAI API, Pinecone, Kubernetes, etc.). Flexible working — remote-first culture with in-person team sessions for collaboration. Career acceleration — opportunities to own projects, lead development, and shape … Science, AI 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 ...

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/… interest in 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 ...

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/… interest in 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 ...