7 of 7 Remote/Hybrid Pinecone Jobs in the UK

frameworks and 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 ...

such as GPT, Claude, 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 ...

Create front-end applications with React, TypeScript, and frameworks like Next.js or Vite. Integrate LLMs (e.g., OpenAI, Anthropic, Mistral) and vector databases (e.g., ChromaDB, Pinecone, PGVector). Deploy solutions using AWS or Azure, Docker, Kubernetes, and Terraform. Implement CI/CD pipelines and monitor LLM performance using tools like Langsmith ...

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 technical ...

required What We're Looking For Essential – Strong Python — production-quality services, not just scripts – Data pipelines and ELT workflows in production – Vector databases (Pinecone, Weaviate, Qdrant or similar) and semantic/hybrid search – LLM API integration in live systems – Docker and containerisation; familiarity with orchestration – API design, security ...

your instinct is to build the solution, not write a process document about it. Nice to Haves Experience with vector databases (e.g., pgvector, Pinecone) or building RAG pipelines. Familiarity with recruitment CRMs (JobAdder, Bullhorn, Vincere, etc.). Experience deploying services on Railway, Render, or similar PaaS platforms. Working knowledge ...

Stack: Deep expertise in Google Cloud Platform (GCP) , Vertex AI , and Gemini Models . AI Frameworks: Strong hands-on experience with LangChain , Vector Databases (Pinecone, Weaviate, etc.), and LLMOps tools. Domain: Experience delivering AI/GenAI use cases within Banking or highly regulated industries is a significant plu Why Apply ...