16 of 16 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 ...

/ML 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 ...

production-ready AI systems. Experience in designing and implementing enterprise-grade AI solutions, including RAG-based solutions with LLMs and vector databases (e.g., Pinecone, Weaviate, FAISS). Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience in full stack development and AI/ ...

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 ...

Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data MLOps & Infrastructure MLOps: Model versioning, monitoring, logging Bias ...

Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. Vector Databases: Experience with and (but not limited to) ChromaDB, Pinecone, PGVector, MongoDB , Qdrant etc. NoSQL: Familiarity with NoSQL databases (e.g., MongoDB preferred). SQL: Experience working with SQL databases like PostgreSQL. Proficient in Git and version ...

Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. Vector Databases: Experience with and (but not limited to) ChromaDB, Pinecone, PGVector, MongoDB , Qdrant etc. NoSQL: Familiarity with NoSQL databases (e.g., MongoDB preferred). SQL: Experience working with SQL databases like PostgreSQL. Proficient in Git and version ...

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 ...

LangChain, 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 ...

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 ...

REST APIs, JSON, and async patterns. Desirable skills/knowledge/experience Experience with vector databases (Cosmos DB with vector search, Redis Enterprise, or Pinecone) and semantic ranking. Knowledge of Azure Machine Learning for training/evaluation pipelines and model registries. Familiarity with Power Platform (AI Builder, Power Automate ...

embeddings, document chunking strategies, indexing, semantic search, and citation/grounding techniques. Experience with vector databases (e.g., Azure Cosmos DB vector search, Redis Enterprise, Pinecone) and reranking strategies. Experience with Git and CI/CD (Azure DevOps or GitHub), unit/integration testing for LLM pipelines, and environment/config ...

using models including GPT-4o/5, Llama3, Claude, Gemini 2.5 Pro, Bard , and enterprise-grade LLM deployments. Implement RAG and CAG architectures using Pinecone, OpenSearch, Google GenAI Search , and custom vector stores. Engineer domain-tuned embeddings using ADA-002, Gecko, Word2Vec, BERT, Sentence Encoder, and topic modelling. AI/… experience: GPT-3.5/4o/5, Llama2/3, Claude, Gemini, Bedrock models, SQuAD fine-tuning, custom RAG agents AI Search & Vector Innovations Pinecone, OpenSearch, LangChain/LangGraph, LangIndex, Vertex AI Search, Vector DBs, RAG pipelines What We're Looking For Proven experience developing production-grade LLM, GenAI ...

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 ...

build systems that scale Experience building and shipping AI agents and LLM-powered systems in production Strong RAG experience; with hands on vector databases (Pinecone, pgvector or similiar) They are based in London with their engineering team operating either hybrid or remote. ⚡ This is a fantastic opportunity sitting right ...