12 of 12 Permanent Weaviate Jobs in 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 ❯

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 ❯

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 ❯

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 ❯

Deep knowledge of cloud infrastructure and services. Experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers). Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS). Experience with RAG (Retrieval-Augmented Generation), LLMOps, or LangChain/LlamaIndex. Proficiency with Infra-as-Code tools like Terraform. Understanding of data pipelines More ❯

solving skills and ability to work in a fast-paced, agile environment. Nice-to-Have Skills: Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, PGVector, etc.). Experience fine-tuning LLMs for domain-specific applications. Knowledge of data privacy, governance, and compliance in AI-driven systems. Previous work in 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 ❯

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 ❯

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... More ❯