1 to 25 of 35 Pinecone Jobs in the UK

Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such as Pinecone, Weaviate or ChromaDB Cloud & DevOps Experience with at least one major cloud platform: AWS (preferred) Bedrock SageMaker Lambda ECS/EKS S3 Or experience within ...

Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such as Pinecone, Weaviate or ChromaDB Cloud & DevOps Experience with at least one major cloud platform: AWS (preferred) Bedrock SageMaker Lambda ECS/EKS S3 Or experience within ...

regularisation, statistics Production ML experience—deploying, serving and monitoring models at scale LLM and generative AI tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience (AWS, GCP, Azure), containerisation ...

deliver that alternative. Relational databases: PostgreSQL, MySQL, or equivalent, schema design, query optimisation, and data modelling. Vector databases: practical production experience with pgvector, Pinecone, Weaviate, or similar for semantic search and RAG pipelines. Graph databases: Neo4j or equivalent; experience modelling domain knowledge as a graph. Demonstrated technical leadership, not necessarily ...

experience with AI system design, architecture, and distributed systems Expertise in API-based backend development (e.g. FastAPI or similar) Experience with vector databases (e.g. Pinecone, Chroma) Experience with agent frameworks (e.g. LangChain, LangGraph, or similar) Strong understanding of evaluation frameworks for AI/agent systems Experience implementing CI/ ...

frameworks (e.g., OpenAI, Azure OpenAI, Anthropic, Hugging Face) Strong understanding of prompt engineering techniques and optimisation strategies Experience working with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) Practical experience with model evaluation, tuning, and performance optimisation Experience integrating AI solutions into APIs, microservices, and front-end applications Strong understanding ...

embeddings, prompt engineering or fine tuning ·Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks ·Experience with vector databases such as Pinecone, Chroma or similar ·API development experience, ideally with FastAPI or similar frameworks ·Knowledge of MLOps, LLMOps, CI/CD or production deployment practices ·Experience designing ...

embeddings, prompt engineering or fine tuning · Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks · Experience with vector databases such as Pinecone, Chroma or similar · API development experience, ideally with FastAPI or similar frameworks · Knowledge of MLOps, LLMOps, CI/CD or production deployment practices · Experience designing ...

continuous integration and deployment tools such as GitLab , GitHub , or Jenkins . Database Management 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. Version Control Proficient ...

continuous integration and deployment tools such as GitLab , GitHub , or Jenkins . Database Management 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. Version Control Proficient ...

using frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, CrewAI or similar agent orchestration frameworks Strong experience designing and optimising retrieval systems, including vector stores (Pinecone, Weaviate, Chroma), graph-based RAG architectures, hybrid retrieval, reranking, and semantic search pipelines Experience with production optimisation for RAG systems, including latency optimisation, token cost ...

extraction, policy summarisation, intelligent routing — including evaluation, guardrails, cost, and latency considerations. Architect retrieval-augmented generation (RAG) solutions using vector-search platforms (e.g., OpenSearch, Pinecone), owning decisions on chunking, embeddings, retrieval quality, and context management. Champion fluent use of AI coding assistants (Claude Code, GitHub Copilot, Cursor, etc.) across ...

Large Language Models (LLMs)Prompt engineering, fine-tuning and Retrieval-Augmented Generation (RAG) LangChain, LangGraph or similar agent frameworks Vector databases such as Pinecone, Chroma or FAISS AI Agents and Generative AI applications Cloud platforms including AWS and/or Azure Modern ML pipelines and MLOps practices Agile delivery methodologies ...

pipeline integration (e.g., GitHub Actions, Jenkins). Modern AI Integration (2026 Trend): Experience integrating LLM APIs (OpenAI, Anthropic) or working with vector databases (Pinecone, Milvus) is highly preferred. Qualifications & Experience Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field (or equivalent practical experience ...

quantitative research environments. • Familiarity with LLM observability and experiment tracking (Weights & Biases, LangSmith, Langfuse, MLflow). Familiarity with RAG and vector databases (pgvector, Pinecone, Weaviate). ...

pipelines and integrating with enterprise systems (REST, Python, SQL, GraphQL, Webhooks etc). Solid understanding of LLMs, Prompt engineering/tuning, Vector DBs (AstraDB, Pinecone, Weaviate etc), RAG pipelines (LlamaIndex, Haystack) and Agent/Workflow Orchestration (LangChain, LangGraph, CrewAI) Knowledge of SLM Finetuning and Distillation is big advantage. Experience ...

DevSecOps practices. Set Yourself Apart... Cloud certifications (e.g. Azure Solutions Architect, Google Professional Cloud Architect). Exposure to MLOps frameworks and vector databases (e.g. Pinecone, Weaviate). Experience contributing to proof‐of‐concepts or MVPs, demonstrating rapid learning and experimentation. Experience supporting production AI/ML solutions, ideally within retail ...

Science, Artificial Intelligence, Machine Learning, or a strongly related quantitative field Hands-on experience with cloud-native ML infrastructure platforms Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models Experience with model serving frameworks (vLLM, TensorRT, Ray) Experience with A/B testing and experimentation frameworks for AI features ...

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 ...

Data quality assessment and cleansing methodologies Token optimization techniques for LLM-based agents Resource-constrained AI model deployment Vector databases and semantic search (e.g., Pinecone, Weaviate, Milvus, Qdrant , and ChromaDB ) Prompt engineering for efficient agent reasoning LLM fine-tuning and instruction optimization Graph databases for network topology and context management ...

leveraging AI/GAI technologies and large language models (LLMs) Advanced AI Integration : Apply experience with retrieval-augmented generation (RAG), vector databases (e.g. Pinecone, Weaviate, FAISS), and enterprise search for AI-driven knowledge discovery Optimize AI Performance : Utilize practical experience designing structured prompts, fine-tuning models, and cost optimization strategies ...

MongoDB/DynamoDB) Experience with CI/CD, microservices, TDD/BDD. Knowledge of secure system design. Desirable (AI & Data) Vector DBs: Milvus, Weaviate, Pinecone Data orchestration: Airflow, Prefect, Dagster Search: ElasticSearch/OpenSearch AI frameworks: LangChain, Hugging Face MLOps: MLflow, Kubeflow If you are looking for an opportunity ...

similar. Experience working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms ...

strategy. What We're Looking For Proven experience delivering production-grade data platforms and retrieval systems. Strong expertise with vector databases such as Qdrant, Pinecone, Weaviate, pgvector, or similar technologies. Experience designing embedding pipelines and retrieval-augmented architectures. Strong SQL and database design skills. Excellent Python development experience. Experience processing ...

just prototypes Demonstrable experience of building and deploying complex AI applications using LLMs and ideally, agentic workflows A familiarity with vector databases (pgvector, ChromaDB, Pinecone or similar) is a plus Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options Excellent opportunities ...