8 of 8 Remote pgvector Jobs in the UK excluding London

motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient in Python (FastAPI) and More ❯

motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient in Python (FastAPI) and More ❯

motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient in Python (FastAPI) and More ❯

motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient in Python (FastAPI) and More ❯

motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient in Python (FastAPI) and More ❯

motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient in Python (FastAPI) and More ❯

motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient in Python (FastAPI) and More ❯

projects, defining new patterns, processes, and tooling from the ground up. Experience with GitHub Actions, Terraform, or similar DevOps tooling. Familiarity with vector databases or hybrid search infrastructure (e.g., pgvector, Pinecone). Experience in data privacy, ethical AI, or governance frameworks. Familiarity with real-time applications using technologies like WebSockets or serverless edge functions. We are united by a shared More ❯