151 to 175 of 182 pgvector Jobs

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, NER models ...

Agent Framework Knowledge of MCP and A2A protocols for agent and tool interoperability Hands-on work with vector databases like Pinecone, Weaviate, Qdrant or pgvector Familiarity with distributed systems, workflow engines (Temporal, Airflow or Dagster) and event-driven architectures Experience with open-source LLMs or Small Language Models for custom ...

search. Summarization or classification applications. Copilot-style assistants. Agentic or multi-step AI workflows. LangChain, LlamaIndex, or similar orchestration frameworks. Vector databases such as pgvector, Qdrant, or Milvus. Ollama, vLLM, or similar model-serving environments. Evaluating LLM output for quality, accuracy, and hallucination risk. Please note: Using ChatGPT ...

scale deployments.Hybrid cloud or cloud‐adjacent patterns (Kubernetes CSI, cloud‐native fabrics, data locality).Experience with one or more vector databases (Milvus, Qdrant, Pinecone, pgVector, OpenSearch/Elasticsearch vectors, etc.), including schema design, ingestion, and operations.Solid understanding of RAG and Generative AI workflows: embeddings, retrieval, reranking, prompt design, context management ...

comfort working with AI tools and prompting. An understanding of point in time data is a strong plus Also desirable: experience with vector databases (pgvector, Pinecone, Weaviate, Qdrant or similar); machine learning experience (PyTorch, TensorFlow, XGBoost/LightGBM) for building, maintaining and extending existing models; Bloomberg API integration to Python ...

native SDKs; sandboxing, permissioning, and human-in-the-loop design Retrieval and knowledge: RAG and Graph RAG at enterprise scale; vector and hybrid search (pgvector, OpenSearch/Elasticsearch, or dedicated stores) including chunking strategy, reranking, and distributed retrieval; knowledge graphs and entity resolution; Text-to-SQL over complex enterprise schemas ...

LANGCHAIN, LANGGRAPH, AND AGENTIC AI FRAMEWORKS/RAG ARCHITECTURE AND ENTERPRISE SEARCH (AZURE AI SEARCH)/OPENAI OR SIMILAR LLM PLATFORMS/VECTOR DATABASES (PGVECTOR, CHROMADB ...

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, air-gapped deployments ...

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, air-gapped deployments ...

loops: planner/executor/verifier patterns, tool‐use schemas, retry + escalation logic. Build retrieval pipelines: chunking strategy, vector DB choice (Pinecone/pgvector/Weaviate), reranking, freshness handling. Stay current on Anthropic + OpenAI release notes; adjust prompts + schemas when APIs evolve. We treat the foundation‐model ...

paved road: self‐hosted LangSmith and LangGraph Platform as the agent runtime and evaluation plane, model providers behind a swappable gateway seam, PostgreSQL with pgvector plus ClickHouse and S3‐compatible object storage as the data platform, Neo4j Enterprise as the semantic knowledge graph, an agent memory plane serving episodic ...

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 applications, analyzing ...

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 applications, analyzing ...

graph models for complex reaction networks, define the semantic ontologies that let AI reason across different chemical data types, and design vector search (e.g. pgvector, Pinecone) for similarity lookups across large molecular sets. Design the telemetry pipeline. Specify streaming ingestion for high-frequency robot and sensor data, with zero loss ...

modern LLMs and tooling (OpenAI/Anthropic/Llama, Hugging Face, LangChain/LlamaIndex, function and tool calling). Retrieval and vector databases (FAISS, pgvector, Pinecone, Weaviate, or similar), and hybrid retrieval that combines graph and vector. Cloud and containers (AWS/GCP/Azure), Docker/Kubernetes, IaC (Terraform … ArangoDB multi-model (graph, document, key-value), AQL, graph algorithms, GraphRAG Models & SDKs:OpenAI, Anthropic, Meta Llama, Hugging Face Retrieval:graph traversal plus FAISS, pgvector, Pinecone, Weaviate; rerankers (ColBERT, cross-encoders) Pipelines & Orchestration:LangChain, LlamaIndex, Ray, Airflow MLOps & Evals:MLflow, Weights & Biases, Ragas, promptfoo, Great Expectations Serving & Infra:vLLM ...

systems, not just prototypes Demonstrable experience of building and deploying complex AI applications using LLMs and ideally, agentic workflows A familiarity with vector databases (pgvector, ChromaDB, Pinecone or similar) is a plus Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options Excellent ...

systems, not just prototypes Demonstrable experience of building and deploying complex AI applications using LLMs and ideally, agentic workflows A familiarity with vector databases (pgvector, ChromaDB, Pinecone or similar) is a plus Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options Excellent ...

compute primitives • Model lifecycle operations: MLflow registry, shadow/A/B/canary patterns, and auto- rollback on golden signal degradation • Vector databases: Pgvector or Qdrant - ANN index strategies, embedding upsert, and query latency tuning under inference load • Strong Python and PyTorch; Flyte or equivalent ML orchestrator • Quantization (nice ...

compute primitives • Model lifecycle operations: MLflow registry, shadow/A/B/canary patterns, and auto- rollback on golden signal degradation • Vector databases: Pgvector or Qdrant - ANN index strategies, embedding upsert, and query latency tuning under inference load • Strong Python and PyTorch; Flyte or equivalent ML orchestrator • Quantization (nice ...

Senior Machine Learning Engineer ££75,000 GBP Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Senior Machine Learning Engineer Location: London (Hybrid) Salary: £75,000 + Bonus + Excellent Benefits Are you ...

methodologies Experience storing and managing JSON objects within PostgreSQL Strong stakeholder communication and collaborative working skills Desirable Skills Experience with PostgreSQL extensions such as: pgvector PostGIS A pache AGE Additional experience with Oracle and/or MS SQL Server Experience supporting data science or data engineering environments Exposure to secure ...

methodologies Experience storing and managing JSON objects within PostgreSQL Strong stakeholder communication and collaborative working skills Desirable Skills Experience with PostgreSQL extensions such as: pgvector PostGIS A pache AGE Additional experience with Oracle and/or MS SQL Server Experience supporting data science or data engineering environments Exposure to secure ...

without:Postgresql dba, core development/maintenance and performance optimisation (sharding, partitions). Experience with clustering, and extensions such as pgvector PostGIS, and AGE very useful.Additional skills in Oracle or MSSQL would also be required. Candidate should have experience in the Latest version of OracleStrong PostgreSQL database management skills:Performance ...

without:Postgresql dba, core development/maintenance and performance optimisation (sharding, partitions). Experience with clustering, and extensions such as pgvector PostGIS, and AGE very useful.Additional skills in Oracle or MSSQL would also be required. Candidate should have experience in the Latest version of OracleStrong PostgreSQL database management skills:Performance ...

Vacancy detailSenior Machine Learning Engineer75,000 GBPHybrid WORKINGLocation: Central London, Greater London – United Kingdom Type: PermanentSenior Machine Learning EngineerLocation: London (Hybrid)Salary: 75,000 + Bonus + Excellent BenefitsAre you passionate about applying Machine Learning ...