1 to 25 of 39 Remote Pinecone Jobs

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 ❯

and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS More ❯

and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS More ❯

for ML models (MLOps best practices). Example Tools & Technologies: Frameworks & Libraries: LangChain, Hugging Face Transformers, PyTorch, TensorFlow, Scikit-learn Agentic AI Tools: OpenAI GPT models, Crew,AI, Cohere, Pinecone (for vector databases), AutoGPT Data Engineering & ML Pipelines: Apache Airflow, MLflow, Kubeflow, dbt, Prefect Cloud & Deployment Platforms: AWS SageMaker, Azure ML, Google Vertex AI APIs & Orchestration: OpenAI API, Anthropic Claude More ❯

CI/CD : Experience with 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 in Git and version control platforms 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 ❯

CI/CD : Experience with 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 in Git and version control platforms 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 ❯

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 ❯

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 ❯

retrieval-augmented generation, prompt management, model orchestration). Work with embeddings, vector stores, and similarity search to enable contextual AI responses. Integrate with vector databases (e.g., FAISS, Weaviate, or Pinecone) to support semantic search and information retrieval. Build scalable APIs and services using FastAPI or similar frameworks. Use tools like MLflow to manage model experimentation, versioning, and deployment. Collaborate closely … in Python, with experience building services using FastAPI or similar frameworks. Working with embeddings for text or document representation and semantic search. Familiarity with vector databases (e.g., FAISS, Weaviate, Pinecone). Understanding of AI infrastructure: versioning, tracking, and deployment with tools like MLflow. Exposure to building production-grade APIs, services, or workflows in an agile, collaborative environment. Awareness of AI 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

up infrastructure using containers, APIs and serverless components Preprocess, chunk and structure unstructured data for optimal use in prompts and context injection Configure and manage vector databases such as Pinecone or Azure AI Search Implement retrieval-augmented generation flows using vector databases and embedding models Develop orchestration logic for multi-step agents and tool-using language models Monitor system performance 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 ❯

building and testing new functionality, troubleshooting customer issues, finding root causes, and developing improvements to ensure maximal user impact and performance. Our RAG system is based on Python and Pinecone and we have deployed a set of open-source models. We interact with our code and data traceability graph through our main application stack which is currently based on Next.js … with and foundational understanding of LLMs (especially open source models), including production deployment Experience with and foundational understanding of non-LLM AI, including production deployment Experience with RAG systems (Pinecone or similar) Strong interest in programming languages, parsing algorithms, interpreters, and compilers Extensive experience in Python, Pandas, and at least one other programming language Experience with and clear understanding of More ❯

building and testing new functionality, troubleshooting customer issues, finding root causes, and developing improvements to ensure maximal user impact and performance. Our RAG system is based on Python and Pinecone and we have deployed a set of open-source models. We interact with our code and data traceability graph through our main application stack which is currently based on Next.js … with and foundational understanding of LLMs (especially open source models), including production deployment Experience with and foundational understanding of non-LLM AI, including production deployment Experience with RAG systems (Pinecone or similar) Strong interest in programming languages, parsing algorithms, interpreters, and compilers Extensive experience in Python, Pandas, and at least one other programming language Experience with and clear understanding of More ❯

building and testing new functionality, troubleshooting customer issues, finding root causes, and developing improvements to ensure maximal user impact and performance. Our RAG system is based on Python and Pinecone and we have deployed a set of open-source models. We interact with our code and data traceability graph through our main application stack which is currently based on Next.js … with and foundational understanding of LLMs (especially open source models), including production deployment Experience with and foundational understanding of non-LLM AI, including production deployment Experience with RAG systems (Pinecone or similar) Strong interest in programming languages, parsing algorithms, interpreters, and compilers Extensive experience in Python, Pandas, and at least one other programming language Experience with and clear understanding of More ❯