9 of 9 Pinecone Jobs in the South East

unsupervised) MLOps/LLMOps and AI observability Hands-on experience building enterprise RAG solutions using LLMs (e.g. OpenAI, Llama, Mistral, Claude) and vector databases (Pinecone, Weaviate, FAISS, etc.) Practical experience with GenAI frameworks such as LangChain, LlamaIndex, and agentic frameworks like AutoGen, CrewAI, LangGraph Strong Python expertise with AI/ ...

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 ...

LangGraph, LangSmith or similar Solid NLP background (tokenisation, embeddings, transformers, BERT-style models, sentiment analysis) Experience integrating vector databases (e.g. Azure AI Search, OpenSearch, Pinecone, Weaviate) Cloud experience on Azure, AWS or GCP Familiarity with MLflow, model evaluation frameworks, observability & monitoring Strong understanding of deploying AI systems into real-world ...

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 ...

experience with LangChain, LangGraph, and Indexify , with a deep understanding of RAG architectures . Expert-level SQL and experience with BigQuery and vector databases (Pinecone, Weaviate, Vertex AI Search). Proven track record in MLOps and deploying ML models at scale. Experience moving LLM-based prototypes into production environments with ...

systems: chunking strategies, document schemas, metadata, hybrid/dense retrieval, re-ranking, and grounding. Manage vector/keyword indexes (e.g., Azure AI Search, pgvector, Pinecone/Weaviate). Develop and deploy advanced NLP, information retrieval, and recommendation systems that enhance Chambers and Partners’ research and product offerings, including document understanding ...

retrieval systems with large language models. Build and maintain applications using LangChain to orchestrate complex AI workflows. Implement and manage vector databases (e.g., FAISS, Pinecone, Weaviate, Milvus) for fast similarity search and retrieval. Develop embedding pipelines for unstructured data using models like Sentence Transformers, OpenAI, or Hugging Face. Collaborate with … Experience with large language models (GPT, BERT, etc.). Fine-tuning and prompt engineering. Experience with vector similarity search. Knowledge of popular vector DBs: Pinecone, Weaviate, FAISS, Vespa, Milvus. Generating and managing embeddings (using models like SentenceTransformers, OpenAI, Hugging Face). Familiarity with LangChain for building LLM-powered applications. Ability ...