Vector Databases Jobs in Bridgewater, MA (NOW HIRING)

LangChain LlamaIndex Hugging Face OpenAI APIs Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS) Experience in RAG (Retrieval-Augmented Generation) implementations. Knowledge of MLOps tools and ...

LangChain LlamaIndex Hugging Face OpenAI APIs Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS) Experience in RAG (Retrieval-Augmented Generation) implementations. Knowledge of MLOps tools and ...

Build retrieval-augmented generation (RAG) systems using Azure AI Search, Amazon Kendra, or vector databases like Pinecone, Weaviate, or FAISS. * Deploy and manage models on Azure Machine Learning ...

Embedding-based retrieval (pgvector, FAISS, vector databases) * Bandits, contextual bandits, or online learning * A/B testing infrastructure design * Causal inference * dbt * Ad-tech or OOH domain ...

Knowledge of AI/ML foundational components: vector databases, feature stores, RAG pipelines, metadata management. * Strong understanding of data modeling (conceptual, logical, physical), master data ...

Knowledge of AI/ML foundational components: vector databases, feature stores, RAG pipelines, metadata management. * Strong understanding of data modeling (conceptual, logical, physical), master data ...

Familiarity with Retrieval-Augmented Generation (RAG) patterns, embedding models, vector databases, and semantic search techniques to ground AI outputs in enterprise content. Experience working with ...

Experience building AI/ML solutions-such as agentic applications, LLM inference, similarity search, vector databases, guardrails, or memory systems. * Strong coding skills in Python or other ...

LangGraph, LangChain, LlamaIndex, MCP and Vector Databases * Infrastructure: AWS or GCP, Docker and Kubernetes Feel free to add a link to your GitHub in your CV so we can understand what you have ...

Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.

Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience with prompt engineering, prompt evaluation, and LLM performance optimization.

Partner with the Al Architect to ensure data, API, and software platforms support Al Engineering patterns such as RAG, semantic search, embeddings, vector databases, Al evaluation workflows, and ...

Establish technical standards for model access, prompt and response handling, context management, retrieval-augmented generation, semantic search, vector databases, observability, cost management ...

Vector databases / embedding-based retrieval systems * Entity extraction, linking, and relationship mapping * Familiarity with modern AI/LLM tooling (e.g., retrieval-augmented generation, prompt ...

... Vector Databases, and Transparent Data Encryption (TDE) for SQL workloads. - Explore and assess emerging technologies such as Fully Homomorphic Encryption (FHE) and Differential Privacy (DP) for AI ...

Hands-on experience with LLMs, vector databases, RAG approaches, and tools * Experience in SaaS/HR tech or with support and digital adoption use cases. * Familiarity with content localization ...

Proven ability to integrate AI systems with event-driven microservices, vector databases/feature stores, and CI/CD pipelines, while leading reference architectures and cross-cloud patterns that scale ...

Familiarity with designing and integrating databases (SQL, NoSQL) and working with vector databases, RAG, and hybrid search approaches. * Prior experience developing agentic AI applications or GenAI ...

Proven ability to integrate AI systems with event-driven microservices, vector databases/feature stores, and CI/CD pipelines, while leading reference architectures and cross-cloud patterns that scale ...

Proven ability to integrate AI systems with event-driven microservices, vector databases/feature stores, and CI/CD pipelines, while leading reference architectures and cross-cloud patterns that scale ...