51 to 75 of 80 Permanent Milvus Jobs

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

enable tool connectivity, enterprise system integration, agent-to-tool communication, and reusable AI workflows. Build and manage vector database solutions using Pinecone, Weaviate, Milvus, FAISS, Chroma, OpenSearch Vector Engine, Azure AI Search, Vertex AI Vector Search, or pgvector. Deploy and optimize LLM/VLLM inference stacks using vLLM, Hugging … with RAG architecture , including chunking strategies, embeddings, vector search, hybrid search, reranking, metadata filtering, and evaluation. Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, OpenSearch, Vertex AI Vector Search, or pgvector. Knowledge of Graph RAG/knowledge graph solutions using Neo4j, Neptune, TigerGraph ...

tuning, or serving embedding models (e.g. sentence‐transformers, bi‐encoders, cross‐encoders), with practical experience setting up and managing vector databases (e.g. Qdrant, Weaviate, Milvus, pgvector) along with understanding trade‐offs e.g. when to use sparse or dense embeddings (or both) etc. Classical NLP training and evaluating text classifiers ...

resolution), or ad exposure data Familiarity with industry content and identity schemas: EIDR, Schema.org VideoObject, DDEX, or equivalent Experience with embedding models, vector databases (Milvus, Pinecone, Weaviate), and GraphRAG architectures (LangChain/LlamaIndex) Familiarity with GNN-based approaches to knowledge graph reasoning or entity resolution a plus Working knowledge ...

resolution), or ad exposure data Familiarity with industry content and identity schemas: EIDR, Schema.org VideoObject, DDEX, or equivalent Experience with embedding models, vector databases (Milvus, Pinecone, Weaviate), and GraphRAG architectures (LangChain/LlamaIndex) Familiarity with GNN-based approaches to knowledge graph reasoning or entity resolution a plus Working knowledge ...

disagreement signals, dataset curation - ideally in autonomous driving, robotics, or perception Experience with embedding and multimodal models (CLIP-style models, VLMs), vector databases (Milvus, FAISS, pgvector), or GPU batch inference at scale We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing ...

disagreement signals, dataset curation - ideally in autonomous driving, robotics, or perception Experience with embedding and multimodal models (CLIP-style models, VLMs), vector databases (Milvus, FAISS, pgvector), or GPU batch inference at scale We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing ...

state of the art for ML Ops, ML infrastructure, including related tools, design patterns, best practices etc.* Experience with vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate) and information retrieval systems and methods.* Familiarity with media content (video, audio) ML pipelines.* Proficiency in Python and common AI/ML libraries ...

Experience with CPU-based inference, model quantization, and performance tuning Vector Databases & RAG Practical experience with open-source vector databases such as Qdrant, Chroma, Milvus, or pgvector Proven implementation of Retrieval-Augmented Generation (RAG) pipelines Experience generating and managing embeddings and metadata filtering Security & Governance Understanding of data privacy ...