11 of 11 Permanent Pinecone Jobs in the UK excluding London

APIs and integrate ML models into web applications using FastAPI, Flask, React, TypeScript, and Node.js. Vector Databases & Search : Implement embeddings and retrieval mechanisms using Pinecone, Weaviate, FAISS, Milvus, ChromaDB, or OpenSearch. Required skills & experience: 3-5+ years in machine learning and software development Proficient in Python, PyTorch or TensorFlow More ❯

APIs and integrate ML models into web applications using FastAPI, Flask, React, TypeScript, and Node.js. Vector Databases & Search : Implement embeddings and retrieval mechanisms using Pinecone, Weaviate, FAISS, Milvus, ChromaDB, or OpenSearch. Required skills & experience: 3-5+ years in machine learning and software development Proficient in Python, PyTorch or TensorFlow More ❯

Deployment: Strong hands-on experience developing and deploying AI/ML models. RAG Expertise: Experience in Retrieval-Augmented Generation and related vector databases (e.g., Pinecone, FAISS, Weaviate). LLMs & NLP: Experience working with LLMs (OpenAI, Anthropic, Hugging Face, etc.), including model tuning, security, and optimization. Regulatory Knowledge: Understanding of AI More ❯

Deployment: Strong hands-on experience developing and deploying AI/ML models. RAG Expertise: Experience in Retrieval-Augmented Generation and related vector databases (e.g., Pinecone, FAISS, Weaviate). LLMs & NLP: Experience working with LLMs (OpenAI, Anthropic, Hugging Face, etc.), including model tuning, security, and optimization. Regulatory Knowledge: Understanding of AI More ❯

Deployment: Strong hands-on experience developing and deploying AI/ML models. RAG Expertise: Experience in Retrieval-Augmented Generation and related vector databases (e.g., Pinecone, FAISS, Weaviate). LLMs & NLP: Experience working with LLMs (OpenAI, Anthropic, Hugging Face, etc.), including model tuning, security, and optimization. Regulatory Knowledge: Understanding of AI More ❯

SageMaker, Bedrock, Lambda, S3, ECS, EKS Full-Stack Integration: Build APIs (FastAPI, Flask) and integrate with React, TypeScript, Node.js Vector Search: Use FAISS, Weaviate, Pinecone, ChromaDB, OpenSearch Required skills & experience: 3–5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or Hugging Face More ❯

SageMaker, Bedrock, Lambda, S3, ECS, EKS Full-Stack Integration: Build APIs (FastAPI, Flask) and integrate with React, TypeScript, Node.js Vector Search: Use FAISS, Weaviate, Pinecone, ChromaDB, OpenSearch Required skills & experience: 3–5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or Hugging Face More ❯

SageMaker, Bedrock, Lambda, S3, ECS, EKS Full-Stack Integration: Build APIs (FastAPI, Flask) and integrate with React, TypeScript, Node.js Vector Search: Use FAISS, Weaviate, Pinecone, ChromaDB, OpenSearch Required skills & experience: 3–5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or Hugging Face More ❯

document-based GenAI solutions, including RAG pipelines, prompt engineering, and integration with internal APIs. Help orchestrate tools using OpenAI function calling, vector databases (e.g. Pinecone, Weaviate), and knowledge graphs. Collaborate on the deployment of AI agents as secure microservices using Azure Kubernetes Services (AKS) and monitor system performance. Draft structured More ❯

to work autonomously, listen to suggestions, make recommendations, focus on delivery. Bonus Points For Experience with Next.js, API data ingestion, or vector databases (e.g., Pinecone, Weaviate, pgvector, qdrant). Exposure to embedding models, LLMs, or hybrid retrieval/generation architectures. Previous projects (personal, academic, or open source) related to AI More ❯

Develop and optimise RAG pipelines using LangChain, LlamaIndex, or Haystack. Build ingestion workflows (OCR, chunking, embedding, semantic search) and integrate with vector databases (FAISS, Pinecone, Qdrant). Ensure seamless integration of GenAI services into business workflows, prioritising security, scalability, and compliance. Collaborate with cross-functional teams (data scientists, architects, engineers More ❯