Vector Databases Jobs in Allen, TX (NOW HIRING)

Data AI Engineer with Vector Databases Location: Plano, TX Key Responsibilities: * Design and build ETL/ELT pipelines and data processing workflows * Develop batch and real-time data pipelines using ...

Production experience with vector databases and designing ingestion + embedding pipelines for both batch and streaming workloads. Hands-on with prompt design, evaluation, LLM orchestration, and RAG ...

Production experience with vector databases and designing ingestion + embedding pipelines for both batch and streaming workloads. * Hands-on with prompt design, evaluation, LLM orchestration, and RAG ...

Working knowledge of retrieval-augmented generation (RAG) pipelines and vector databases Roles & Responsibilities • Build and tune LLM-based applications using platforms like Vertex, GPT, Lamma ...

The ideal candidate will have hands-on expertise in prompt engineering, fine-tuning LLMs, and working with LangChain and vector databases , while also ensuring robust API and backend development on ...

The ideal candidate will have hands-on expertise in prompt engineering, fine-tuning LLMs, and working with LangChain and vector databases, while also ensuring robust API and backend development on ...

Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models. * Integrate and work with LLMs such as Anthropic Claude, Google Gemini, and other ...

Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate). Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Familiarity ...

Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate). * Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)

Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate). Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Familiarity ...

... vector database. o Serve as the subject matter expert on data sources, liaising with data owners to understand structures, access patterns, and semantics. o Ensure the data ingestion pipeline is ...

Architect and deliver end-to-end LLM-powered applications and agentic workflows using Python Design and implement RAG pipelines over enterprise data using embeddings and vector databases * Build ...

Vector Databases & Retrieval Pipelines: Implement and maintain vector stores (OpenSearch, Pinecone, Milvus, Qdrant) and design efficient similarity search, retrieval workflows, and indexing ...

The ideal candidate will have a solid background in machine learning along with handson expertise in LLMs, RAG, embeddings, vector databases, and Agentic AI frameworks such as CrewAI, AutoGen ...

The ideal candidate will have a solid background in machine learning along with hands‐on expertise in LLMs, RAG, embeddings, vector databases, and Agentic AI frameworks such as CrewAI, AutoGen ...

Vector Databases & Retrieval Pipelines: Implement andmaintainvector stores (OpenSearch, Pinecone, Milvus,Qdrant) and design efficient similarity search, retrieval workflows, and indexing strategies.

RAG & Vector Databases * LangGraph, Agents SDK, Google ADK * Docker, Kubernetes, CI/CD * AWS, Azure, or GCP * AI Governance & Observability * Cursor, Windsurf, Codex Key Responsibilities * Define AI ...

PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt ...

PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt ...

PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt ...