76 to 100 of 343 Retrieval-Augmented Generation Jobs in London

Mistral APIs LLM Frameworks: LangChain, LlamaIndex – for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data With a focus within Energy Trading, Oil & Gas, Financial Markets and Commodities, we offer a transparent Recruitment Service that has proven More ❯

Mistral APIs LLM Frameworks: LangChain, LlamaIndex – for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data With a focus within Energy Trading, Oil & Gas, Financial Markets and Commodities, we offer a transparent Recruitment Service that has proven More ❯

Mistral APIs LLM Frameworks: LangChain, LlamaIndex – for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data With a focus within Energy Trading, Oil & Gas, Financial Markets and Commodities, we offer a transparent Recruitment Service that has proven More ❯

Mistral APIs LLM Frameworks: LangChain, LlamaIndex – for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data With a focus within Energy Trading, Oil & Gas, Financial Markets and Commodities, we offer a transparent Recruitment Service that has proven More ❯

experts across 230 locales, to create high-quality pre-trained datasets, fine-tuned industry-specific Large Language Models(LLMs), and Retrieval-Augmented Generation (RAG) pipelines supported by vector databases. Our innovations can reduce Generative Artificial Intelligence(Gen AI) costs by up to 80% and bring Gen AI solutions to market 50% faster. Our mission More ❯

experts across 230 locales, to create high-quality pre-trained datasets, fine-tuned industry-specific Large Language Models(LLMs), and Retrieval-Augmented Generation (RAG) pipelines supported by vector databases. Our innovations can reduce Generative Artificial Intelligence(Gen AI) costs by up to 80% and bring Gen AI solutions to market 50% faster. Our mission More ❯

experts across 230 locales, to create high-quality pre-trained datasets, fine-tuned industry-specific Large Language Models(LLMs), and Retrieval-Augmented Generation (RAG) pipelines supported by vector databases. Our innovations can reduce Generative Artificial Intelligence(Gen AI) costs by up to 80% and bring Gen AI solutions to market 50% faster. Our mission More ❯

experts across 230 locales, to create high-quality pre-trained datasets, fine-tuned industry-specific Large Language Models(LLMs), and Retrieval-Augmented Generation (RAG) pipelines supported by vector databases. Our innovations can reduce Generative Artificial Intelligence(Gen AI) costs by up to 80% and bring Gen AI solutions to market 50% faster. Our mission More ❯

practises, including metadata tagging, version control, and retention policies. - Familiarity with AI integration workflows, including semantic indexing, vector databases, and retrieval-augmented generation (RAG). - Knowledge of Microsoft Graph API, Azure AI Foundry, and Copilot integration is a strong plus. - Experience with Filament, LlamaIndex, or similar AI connectors. - Familiarity with enterprise-grade security protocols More ❯

experts across 230 locales, to create high-quality pre-trained datasets, fine-tuned industry-specific Large Language Models(LLMs), and Retrieval-Augmented Generation (RAG) pipelines supported by vector databases. Our innovations can reduce Generative Artificial Intelligence(Gen AI) costs by up to 80% and bring Gen AI solutions to market 50% faster. We aim More ❯

ReAct, Tree-of-Thoughts, and more. Deploy AI/ML pipelines using Azure ML, AWS SageMaker, Vertex AI, or Databricks. Integrate LLMs into production apps using LangChain, LlamaIndex, and RAG architectures. Build APIs and microservices for scalable AI deployment. Use AI-powered dev tools like GitHub Copilot, Cursor, and Codeium to speed up iteration. Apply MLOps/LLMOps practices with More ❯

LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems and create areas for improvement Degree in Computer Science, AI, Big Data, or equivalent If interested, and the above applies to More ❯

LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems and create areas for improvement Degree in Computer Science, AI, Big Data, or equivalent If interested, and the above applies to More ❯

LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems and create areas for improvement Degree in Computer Science, AI, Big Data, or equivalent If interested, and the above applies to More ❯

LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems and create areas for improvement Degree in Computer Science, AI, Big Data, or equivalent If interested, and the above applies to More ❯

GCP) Experience integrating AI or LLM APIs and open-source models into live products Hands-on experience building or maintaining Retrieval-Augmented Generation (RAG) pipelines Tremendous opportunity offering plenty of scope for career progression in a friendly, innovative environment where you'll be able to bring ideas, stay up to date with the latest More ❯

of web content Prototyping algorithms to optimise ad performance and bidding logic Applying modern LLM techniques — from prompt engineering to retrieval-augmented generation (RAG) Working cross-functionally with engineers, product and commercial teams to bring ideas to life What they’re looking for: 1–3 years’ experience in applied ML/AI (or equivalent More ❯

of web content Prototyping algorithms to optimise ad performance and bidding logic Applying modern LLM techniques — from prompt engineering to retrieval-augmented generation (RAG) Working cross-functionally with engineers, product and commercial teams to bring ideas to life What they’re looking for: 1–3 years’ experience in applied ML/AI (or equivalent More ❯

of web content Prototyping algorithms to optimise ad performance and bidding logic Applying modern LLM techniques — from prompt engineering to retrieval-augmented generation (RAG) Working cross-functionally with engineers, product and commercial teams to bring ideas to life What they’re looking for: 1–3 years’ experience in applied ML/AI (or equivalent More ❯

of web content Prototyping algorithms to optimise ad performance and bidding logic Applying modern LLM techniques — from prompt engineering to retrieval-augmented generation (RAG) Working cross-functionally with engineers, product and commercial teams to bring ideas to life What they’re looking for: 1–3 years’ experience in applied ML/AI (or equivalent More ❯

Software Engineer – Generative AI to design, develop, and deploy advanced AI solutions, including fine-tuning Vision and Language Models (V/LLMs) and implementing Graph-based RAG (Retrieval-Augmented Generation) systems. As a key member of our Global Supply Chain GenAI Team , you will drive the technical implementation of scalable, secure, and efficient Generative … experience in at least two AI domains such as NLP, NLG, Computer Vision, Machine Learning, or GenAI . Proven experience with fine-tuning and training LLMs , and developing Graph RAG solutions in production environments. Technical Expertise: Proficiency in cloud platforms – particularly Microsoft Azure and Databricks . Experience with tools and services such as: Azure Machine Learning, Azure AI Services, Azure More ❯

Software Engineer – Generative AI to design, develop, and deploy advanced AI solutions, including fine-tuning Vision and Language Models (V/LLMs) and implementing Graph-based RAG (Retrieval-Augmented Generation) systems. As a key member of our Global Supply Chain GenAI Team , you will drive the technical implementation of scalable, secure, and efficient Generative … experience in at least two AI domains such as NLP, NLG, Computer Vision, Machine Learning, or GenAI . Proven experience with fine-tuning and training LLMs , and developing Graph RAG solutions in production environments. Technical Expertise: Proficiency in cloud platforms – particularly Microsoft Azure and Databricks . Experience with tools and services such as: Azure Machine Learning, Azure AI Services, Azure More ❯

Design, develop, and refine prompts to maximize the accuracy and effectiveness of GenAI models. Utilize techniques like few-shot prompting, chain-of-thought, and RAG (Retrieval Augmented Generation) to improve model performance within banking applications. Iteratively test and refine prompts based on the evaluation of AI outputs to enhance model performance. Manage the full … Profile Essential Skills/Knowledge/Experience: Strong understanding of Large Language Models (LLMs), including architectures, capabilities, and limits. Familiarity with different GenAI model types, such as text generation, summarization, and question answering. Knowledge of model hallucinations, bias, and context … windows. Mastery of prompting strategies such as zero-shot, few-shot, chain-of-thought (CoT), tree-of-thought (ToT), and self-consistency. Expertise in Retrieval Augmented Generation (RAG) architecture and implementation to integrate external, up-to-date, and proprietary data sources. Knowledge of prompt templating, variable injection, and dynamic prompt generation. Strong SQL skills More ❯

CrewAI, LangGraph, ReAct, BabyAGI). Background in human-AI interaction, conversational UX, or simulation environments. Knowledge of vector databases or retrieval-augmented generation (RAG). Understanding of the ethical, social, and safety considerations of autonomous AI systems. NB: Successful applicant will be brought on board with a completed BPSS check and be eligible for More ❯

platforms, not research or PoC Deep background in intelligent document processing, OCR, or data extraction pipelines Technical leadership in designing retrieval-augmented generation (RAG) or agentic AI frameworks Experience deploying models in latency-sensitive, compliance-heavy environments Strong engineering foundation, Python, Kubernetes, Rust, vector databases, cloud-native deployment Experience building proprietary products Deep experience More ❯