1 to 25 of 80 Milvus Jobs

hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI).Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks (LangChain, LangGraph, Semantic Kernel).Data pipelines: data lake/lakehouse architectures, ETL/ELT, and data quality/lineage tooling that ...

hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI).Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks (LangChain, LangGraph, Semantic Kernel).Data pipelines: data lake/lakehouse architectures, ETL/ELT, and data quality/lineage tooling that ...

management, prompt engineering, and Retrieval-Augmented Generation (RAG). Data Analytics: Familiarity with real-time data streaming (e.g., Kafka) and vector databases (e.g., Pinecone, Milvus, Qdrant). Quantization: Experience with model compression techniques like quantization (INT8/FP4), pruning, and distillation for edge deployment. #J-18808-Ljbffr ...

Ph.D.). NLP & LLMs: Hands-on experience fine-tuning, evaluating, and deploying open-source and proprietary LLMs, embedding models, and vector databases (e.g., Pinecone, Milvus, Qdrant, FAISS). Programming & Frameworks: Proficiency in Python, PyTorch, TensorFlow, LangChain, LlamaIndex, and modern API frameworks (FastAPI, RESTful APIs). Data Pipelines & Databases: Experience ...

solving and communication skills. Preferred Qualifications Experience with CrewAI, AutoGen, Semantic Kernel, or similar frameworks. Experience with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or FAISS. Experience implementing RAG architectures. Familiarity with LangSmith, Weights & Biases, Arize AI, or other LLM observability platforms. Experience with Docker, Kubernetes, CI/ ...

solving and communication skills. Preferred Qualifications Experience with CrewAI, AutoGen, Semantic Kernel, or similar frameworks. Experience with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or FAISS. Experience implementing RAG architectures. Familiarity with LangSmith, Weights & Biases, Arize AI, or other LLM observability platforms. Experience with Docker, Kubernetes, CI/ ...

dialogue management. Prompt engineering and Retrieval-Augmented Generation (RAG) . Real-time data streaming platforms such as Kafka . Vector databases including Pinecone, Milvus or Qdrant . Model compression and optimisation techniques including INT8/FP4 quantisation, pruning and knowledge distillation . Deploying machine learning models to resource-constrained ...

experience with LLMs (OpenAI, Anthropic, Meta, Mistral, etc.) and frameworks like LangChain or LlamaIndex. Strong knowledge of RAG architectures, vector databases (Pinecone, Weaviate, Chroma, Milvus, Supabase), and semantic search. Experience with TTS/STT systems (OpenAI Whisper, Coqui TTS, ElevenLabs). Hands-on with generative image models (GPT-Image ...

distributed data platforms and scalable pipelines. Excellent knowledge of PostgreSQL (or similar relational databases) and NoSQL databases. Experience with vector databases such as Qdrant, Milvus or pgvector . Familiarity with technologies such as Apache Spark, Airflow, Kafka, Elasticsearch/OpenSearch, Pandas and Polars . Strong understanding of data modelling ...

applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning or prompt engineering of state-of-the-art Large Language Models (LLMs). Extreme Ownership: High ...

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 ...