17 of 17 Remote Pinecone Jobs in London

custom LLM integrations). Exposure to AI ethics, data privacy, and compliance regulations. Prior experience in multi-agent systems or autonomous AI workflows. Hands-on experience with vector databases (Pinecone, Weaviate, FAISS) and AI embeddings. Remote WorkingSome remote working CountryUnited Kingdom LocationWC1 Job TypeContract or Permanent Start DateApr-Jul 25 Duration9 months initial or permanent Visa RequirementApplicants must be eligible More ❯

/or LLM-powered applications in production environments. Proficiency in Python and ML libraries such as PyTorch, Hugging Face Transformers, or TensorFlow. Experience with vector search tools (e.g., FAISS, Pinecone, Weaviate) and retrieval frameworks (e.g., LangChain, LlamaIndex). Hands-on experience with fine-tuning and distillation of large language models. Comfortable with cloud platforms (Azure preferred), CI/CD tools More ❯

prompt engineering, and deployment Python Proficiency : Strong skills with ML frameworks (TensorFlow, PyTorch) and LLM tools (Hugging Face, LangChain, OpenAI APIs) Vector Understanding : Solid knowledge of embeddings, vector databases (Pinecone, Weaviate, FAISS), and RAG pipelines NLP Fundamentals : Text preprocessing, language modelling, and semantic similarity Cloud Experience : AWS ecosystem knowledge (SageMaker, Lambda, etc.) Production Ready : ETL pipelines, version control, Agile methodologies More ❯

flows, compliance, user segmentation, etc.) Technical Skills: Proficient in Python, SQL, and data science libraries (Pandas, NumPy, Scikit-learn, Hugging Face Transformers) Familiarity with embedding models, vector databases (e.g., Pinecone, FAISS, Weaviate) Experience with cloud platforms (AWS, GCP, or Azure) and MLOps pipelines Solid understanding of NLP, LLM fine-tuning, and prompt engineering Preferred Qualifications Familiarity with customer analytics and More ❯

What you’ll do Design & build backend micro‐services (Python/FastAPI) that power RAG pipelines, user queries, and analytics. Develop retrieval infrastructure : orchestrate embedding generation, vector databases (PGVector, Pinecone, Weaviate), and hybrid search. Implement evaluation framework for search quality and answer accuracy (BLEU/ROUGE, human‐in‐the‐loop, automatic hallucination checks). Deploy & monitor services on GCP (Cloud … ship weekly increments. Champion best practices in testing, secure data handling (NHS DSPT), and GDPR compliance. Tech you’ll use Python • FastAPI • LangChain/LlamaIndex • PostgreSQL + PGVector • Redis • Pinecone/Weaviate • Vertex AI • Cloud Run • Docker • Terraform • Prometheus/Grafana • GitHub Actions What we’re looking for Master’s degree in Computer Science, Software Engineering, or related field; or More ❯

large-scale infrastructure, and modern backend development using Java, Python, Golang, Spring Boot, Flask, and Kubernetes. We focus on integrating RAG-powered LLMs, implementing advanced vector search (FAISS, Milvus, Pinecone), and building scalable and high-performance AI-driven solutions. You Might Be a Good Fit If You: Have deep hands-on software engineering expertise in Java or Python Thrive in … applications using Java, Python, and modern backend frameworks Integrate LLMs into enterprise-scale systems using internal frameworks and libraries Design and implement vector search solutions using FAISS, Milvus, and Pinecone Build scalable APIs and backend services using Spring Boot, Flask, and FastAPI Optimize data storage and retrieval with PostgreSQL/MongoDB and distributed databases Deploy and manage cloud-native applications … Succeed in This Role: Proficiency in Java or Python for backend development Strong knowledge of Spring Boot, Flask, FastAPI, and API design Experience with vector search frameworks (FAISS, Milvus, Pinecone) Expertise in Kubernetes and Docker for scalable deployment Understanding of authentication & security frameworks (Spring Security, SSO) Hands-on experience with PostgreSQL and distributed storage Experience with Maven or Gradle for More ❯

Sub, and Vertex AI. Support AI engineers by managing structured and unstructured data ingestion, embedding pipelines, and vector database integrations. Implement retrieval-augmented generation (RAG) systems using tools like Pinecone, FAISS, Chroma, or PostgreSQL. Develop infrastructure to support short- and long-term memory in autonomous agents. Work with AI orchestration frameworks (LangChain, LangGraph, CrewAI) to ensure reliable data integration and … strong data governance, access control, and compliance practices. Tech Stack: Languages: Python, SQL Cloud: Google Cloud Platform (BigQuery, Dataflow, Vertex AI, Cloud Run, Pub/Sub) Databases: PostgreSQL, BigQuery, Pinecone, FAISS, Chroma Tools: dbt, Airflow, Terraform, Docker, GitHub Actions AI Frameworks: LangChain, LangGraph, LangFlow, CrewAI, OpenAI APIs What We’re Looking For: Strong experience building and maintaining data systems on More ❯

Sub, and Vertex AI. Support AI engineers by managing structured and unstructured data ingestion, embedding pipelines, and vector database integrations. Implement retrieval-augmented generation (RAG) systems using tools like Pinecone, FAISS, Chroma, or PostgreSQL. Develop infrastructure to support short- and long-term memory in autonomous agents. Work with AI orchestration frameworks (LangChain, LangGraph, CrewAI) to ensure reliable data integration and … strong data governance, access control, and compliance practices. Tech Stack: Languages: Python, SQL Cloud: Google Cloud Platform (BigQuery, Dataflow, Vertex AI, Cloud Run, Pub/Sub) Databases: PostgreSQL, BigQuery, Pinecone, FAISS, Chroma Tools: dbt, Airflow, Terraform, Docker, GitHub Actions AI Frameworks: LangChain, LangGraph, LangFlow, CrewAI, OpenAI APIs What We’re Looking For: Strong experience building and maintaining data systems on More ❯

Sub, and Vertex AI. Support AI engineers by managing structured and unstructured data ingestion, embedding pipelines, and vector database integrations. Implement retrieval-augmented generation (RAG) systems using tools like Pinecone, FAISS, Chroma, or PostgreSQL. Develop infrastructure to support short- and long-term memory in autonomous agents. Work with AI orchestration frameworks (LangChain, LangGraph, CrewAI) to ensure reliable data integration and … strong data governance, access control, and compliance practices. Tech Stack: Languages: Python, SQL Cloud: Google Cloud Platform (BigQuery, Dataflow, Vertex AI, Cloud Run, Pub/Sub) Databases: PostgreSQL, BigQuery, Pinecone, FAISS, Chroma Tools: dbt, Airflow, Terraform, Docker, GitHub Actions AI Frameworks: LangChain, LangGraph, LangFlow, CrewAI, OpenAI APIs What We’re Looking For: Strong experience building and maintaining data systems on More ❯

developer tools, open-source culture, and improving developer workflows. Excellent communication and collaboration skills in a remote-first environment. Experience contributing to open-source AI projects. Experience with LangChain, Pinecone, or similar AI frameworks/infrastructure. Past experience building AI features into developer platforms or tools. Benefits Our entire company is distributed, so we take remote work seriously. If you More ❯

building complex architectures from MVP to production Solid hands-on experience with AI/LLM applications and model deployment Comfortable across front-end (HTML, CSS, Tailwind) and back-end (Pinecone, microservices, serverless) Brownie points: SEO know-how Deeper AI/ML chops (Colab, Streamlit, FastAPI, PyTorch, etc.) Entrepreneurial streak and previous startup exposure Ability to pivot quickly and learn on More ❯

knowledge platform. What You’ll Do: Build and scale backend services (Python/FastAPI) for ingesting, indexing, and serving medical content. Develop retrieval infrastructure using vector databases (e.g. PGVector, Pinecone). Deploy on GCP (Cloud Run, Vertex AI) with Terraform, CI/CD, and observability tools. Collaborate across product, mobile, and clinical teams to ship weekly. Ensure secure, compliant data More ❯

knowledge platform. What You’ll Do: Build and scale backend services (Python/FastAPI) for ingesting, indexing, and serving medical content. Develop retrieval infrastructure using vector databases (e.g. PGVector, Pinecone). Deploy on GCP (Cloud Run, Vertex AI) with Terraform, CI/CD, and observability tools. Collaborate across product, mobile, and clinical teams to ship weekly. Ensure secure, compliant data More ❯

Bleu, Perplexity and/or others for prompt and model optimisations. Comfortable working with databases (relational & vector), and large-scale data sets and pipelines (e.g. AWS Glue, Redshift, RDS, Pinecone, Opensearch). Hands-on experience with AI Cloud Infrastructure for MLOps (e.g.Google Vertex AI/AWS Bedrock), including deploying AI applications and managing AI cloud-based services. Expert knowledge of More ❯

TrueLayer Design & build pipelines to analyze transaction data + user conversations Use embedding models (OpenAI, Cohere, etc.) to vectorize user data Store and query vectors using vector databases (e.g. Pinecone, Qdrant) Architect the backend with Node.js or Python (FastAPI/Django) Own end-to-end security and compliance (OAuth2, GDPR, secure storage) Collaborate on the AI recommendation engine that powers … React Native (for Android & iOS) and Python Experience with Open Banking APIs (TrueLayer, Yapily, Salt Edge, etc.) Built or contributed to LLM-based recommendation systems Worked with vector databases (Pinecone, Weaviate, FAISS, Chroma) Familiar with embedding models (e.g. OpenAI, Sentence Transformers) Understands secure data practices (encryption, secure tokens, GDPR) This is a brilliant opportunity for someone who wants to contribute More ❯

TrueLayer Design & build pipelines to analyze transaction data + user conversations Use embedding models (OpenAI, Cohere, etc.) to vectorize user data Store and query vectors using vector databases (e.g. Pinecone, Qdrant) Architect the backend with Node.js or Python (FastAPI/Django) Own end-to-end security and compliance (OAuth2, GDPR, secure storage) Collaborate on the AI recommendation engine that powers … React Native (for Android & iOS) and Python Experience with Open Banking APIs (TrueLayer, Yapily, Salt Edge, etc.) Built or contributed to LLM-based recommendation systems Worked with vector databases (Pinecone, Weaviate, FAISS, Chroma) Familiar with embedding models (e.g. OpenAI, Sentence Transformers) This is a brilliant opportunity for someone who wants to contribute more than just writing code. The business are More ❯

Twilio/WhatsApp Business API. Proven ability to work with LLMs (OpenAI, Claude, Mistral, etc.) in production environments. Understanding of prompt engineering, context window strategies, and vector memory (e.g., Pinecone, ChromaDB). Experience with AI pair programming tools such as Cursor AI, GitHub Copilot, or Cody (non-negotiable). Comfortable embedding dashboards using tools like Streamlit, Superset, or Metabase. Experience More ❯