7 of 7 Weaviate Jobs in the UK excluding London

and integrate ML models into web applications using FastAPI, Flask, React, TypeScript, and Node.js. Vector Databases & Search : Implement embeddings and retrieval mechanisms using Pinecone, Weaviate, FAISS, Milvus, ChromaDB, or OpenSearch. Required skills & experience: 3-5+ years in machine learning and software development Proficient in Python, PyTorch or TensorFlow or More ❯

and integrate ML models into web applications using FastAPI, Flask, React, TypeScript, and Node.js. Vector Databases & Search : Implement embeddings and retrieval mechanisms using Pinecone, Weaviate, FAISS, Milvus, ChromaDB, or OpenSearch. Required skills & experience: 3-5+ years in machine learning and software development Proficient in Python, PyTorch or TensorFlow or More ❯

retrieval pipelines over structured and unstructured health data (EHRs, patient notes, device logs, clinical documentation). Develop indexing strategies using vector databases (e.g., FAISS, Weaviate, Pinecone) and embedding models (e.g., BioBERT, ClinicalBERT). Integrate RAG outputs into user-facing applications, ensuring responses are grounded, reliable, and privacy-compliant. Work closely More ❯

IOI, Top Coder, Kaggle). Technical Skills : Expertise in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch), Generative AI technologies, and libraries like Langchain, Weaviate, Langgraph, LlamaIndex. Track Record : Demonstrated success in applying data science and machine learning to solve real-world, business-critical problems. Collaboration : Excellent communication and collaboration More ❯

with SageMaker, Bedrock, Lambda, S3, ECS, EKS Full-Stack Integration: Build APIs (FastAPI, Flask) and integrate with React, TypeScript, Node.js Vector Search: Use FAISS, Weaviate, Pinecone, ChromaDB, OpenSearch Required skills & experience: 3–5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or Hugging More ❯

based GenAI solutions, including RAG pipelines, prompt engineering, and integration with internal APIs. Help orchestrate tools using OpenAI function calling, vector databases (e.g. Pinecone, Weaviate), and knowledge graphs. Collaborate on the deployment of AI agents as secure microservices using Azure Kubernetes Services (AKS) and monitor system performance. Draft structured documentation More ❯

hands-on experience developing and deploying AI/ML models. RAG Expertise: Experience in Retrieval-Augmented Generation and related vector databases (e.g., Pinecone, FAISS, Weaviate). LLMs & NLP: Experience working with LLMs (OpenAI, Anthropic, Hugging Face, etc.), including model tuning, security, and optimization. Regulatory Knowledge: Understanding of AI governance, compliance More ❯