1 to 25 of 169 Retrieval-Augmented Generation Jobs in London

source control and the Azure cloud. In this role you will You'll have the opportunity to work on a mixture of the following: Generative AI Design and develop RAG based applications. LLM fine-tuning, including preparation of training sets from internal data Agent based applications Evaluating use-case specific LLMs AI/ML NLP: Named Entity Recognition across a … looking for professionals with these required skills to achieve our goals: Bachelor's degree in computer science Extensive experience working in AI/ML Generative AI: Demonstratable experience of RAG, including chunking strategies, vectorising and indexing data, retrieval strategies and reranking, prompting strategies, function calling. Our current tech-stack is OpenAI, LangChain, Azure AI, Python, pg_vector, Sinequa. More ❯

role, you'll work closely with ML scientists, data engineers, and product teams to help bring innovative solutions-such as retrieval-augmented generation (RAG) systems, multi-agent architectures , and AI agent workflows -into production. As a Senior Machine Learning Engineer, you'll play a key role in developing and integrating cutting-edge AI solutions … a highly collaborative and fast-moving environment where your contributions will directly shape both the future of our platform and your own growth. Key Responsibilities Design, build, and deploy RAG systems , including multi-agent and AI agent-based architectures for production use cases. Contribute to model development processes including fine-tuning, parameter-efficient training (e.g., LoRA, PEFT), and distillation . … related technical discipline. Strong foundation in machine learning and data science fundamentals -including supervised/unsupervised learning, evaluation metrics, data preprocessing, and feature engineering. Proven experience building and deploying RAG systems and/or LLM-powered applications in production environments. Proficiency in Python and ML libraries such as PyTorch, Hugging Face Transformers , or TensorFlow. Experience with vector search tools (e.g. More ❯

robust agentic workflows enabling AI agents to interact autonomously with data sources and external APIs using advanced prompt engineering and retrieval-augmented generation (RAG) Fine-tune and optimize pre-trained large language models and multi-modal models for targeted use cases, ensuring high performance and low latency in production. Implement distributed training and scalable More ❯

techniques including test-driven development (TDD), Behaviour-driven development (BDD), integration testing and performance testing Some experience with AI tools (one of more of) Python, LLM(Large Language models), RAG, Langchain Set Yourself apart with: Bachelor's/Master's degree in Computer Science or related field Experienceof working on large scale, complex, and distributed applications in an Agile environment More ❯

APIs, or other LLM orchestration tools. A solid understanding of tokenization, embedding models, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) pipelines. Experience designing and evaluating LLM-powered systems such as chatbots, summarization tools, content generation workflows, or intelligent data extraction pipelines. Deep understanding of NLP fundamentals: text preprocessing More ❯

APIs, or other LLM orchestration tools. A solid understanding of tokenization, embedding models, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) pipelines. Experience designing and evaluating LLM-powered systems such as chatbots, summarization tools, content generation workflows, or intelligent data extraction pipelines. Deep understanding of NLP fundamentals: text preprocessing More ❯

to the highest standards. You'll be part of a multidisciplinary team focused on delivering enterprise-grade AI capabilities, including generative AI, agentic AI, LLMs and RAG (retrieval-augmented generation). The AI Engineer will optimise prompts to generative AI models across NiCE's Proactive AI Agent applications, working with several groups in the More ❯

with product and domain experts to identify compelling solutions at the intersection of user needs and technical feasibility. Our team in Labs Legal Tech is designing the next generation of Legal Technology globally. We drive AI innovation for Thomson Reuters' LegalTech Products and features, including CoCounsel Core , CoCounsel Drafting , Practical Law , HighQ , Legal Tracker , Document Intelligence , Contract Express … projects, Practical experience using generative AI technologies (prompt engineering, in-context learning, chain-of-thoughts, prompt optimization, auto-evaluation, function calling, controlled generation, etc.) Practical experience using RAG frameworks, pre-training/fine-tuning language models, and data curation/generation for training/fine-tuning language models, Practical experience using agentic frameworks (such as LangGraph More ❯

Python Proficiency : Strong skills with ML frameworks (TensorFlow, PyTorch) and LLM tools (Hugging Face, LangChain, OpenAI APIs) Vector Understanding : Solid knowledge of embeddings, vector databases (Pinecone, Weaviate, FAISS), and RAG pipelines NLP Fundamentals : Text preprocessing, language modelling, and semantic similarity Cloud Experience : AWS ecosystem knowledge (SageMaker, Lambda, etc.) Production Ready : ETL pipelines, version control, Agile methodologies It would be a More ❯

rapid iteration, prompt engineering, and practical application. You'll fine-tune and optimize foundation models, craft sophisticated multi-agent systems, and invent novel solutions to power the next generation of voice intelligence. What You'll Do Integrate AI solutions into existing products and workflows Collaborate with cross-functional teams to understand business requirements and translate them into technical … AWS, Google Cloud, or Azure Knowledge of Kubernetes and containerization technologies Experience with data science and ML engineering Familiarity with retrieval-augmented generation (RAG) The requirements listed in the job descriptions are guidelines. You don't have to satisfy every requirement or meet every qualification listed. If your skills are transferable we would still More ❯

work closely with product and domain experts to identify compelling solutions at the intersection of user needs and technical feasibility. Our team is responsible for designing the next generation of risk and fraud investigation software. We own AI innovation for Thomson Reuters' core Risk and Fraud products, including CLEAR , CLEAR Adverse Media , and CLEAR Risk Inform . About … NLP/ML/Knowledge Graph/GenAI systems for commercial applications Practical experience with traditional and state-of-the-art NLP methods, Knowledge Graph algorithms, and GenAI (including RAG and agentic frameworks) Experience writing production code and ensuring well-managed software delivery Demonstrable experience translating complex problems into successful AI applications Outstanding communication, problem-solving, and analysis skills Collaborating More ❯

communication of complex ideas. Ability to work independently and collaboratively. Preferred Skills: Experience building scalable applications with LLMs using frameworks like LangChain, LlamaIndex, Hugging Face, etc. Deep knowledge of RAG implementation and enhancements. Benefits & perks (UK full-time employees): Generous PTO and holidays. Comprehensive medical and dental insurance. Paid parental leave (12 weeks). Fertility and family planning support. Early More ❯

architecture of LLMs. Foundational knowledge of diffusion models for image generation. Can display and present completed project/s using LLMs with a focus on any of the following: RAG, Agentic-RAG, fine-tuning Some experience or familiarity with deploying applications in the Cloud using services such as AWS or Azure. Proven track record in securing web/API applications. More ❯

architecture of LLMs. Foundational knowledge of diffusion models for image generation. Can display and present completed project/s using LLMs with a focus on any of the following: RAG, Agentic-RAG, fine-tuning Some experience or familiarity with deploying applications in the Cloud using services such as AWS or Azure. Proven track record in securing web/API applications. More ❯

architecture of LLMs. Foundational knowledge of diffusion models for image generation. Can display and present completed project/s using LLMs with a focus on any of the following: RAG, Agentic-RAG, fine-tuning Some experience or familiarity with deploying applications in the Cloud using services such as AWS or Azure. Proven track record in securing web/API applications. More ❯

Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline Understanding of NLP algorithms and techniques and/or experience with Large Language Models (fine tuning, RAG, agents) Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.) Have experience productionising machine learning models Are an expert in one of predictive modeling More ❯

Practical knowledge in data wrangling, handling, processing, integrating, and analyzing large heterogeneous data sets related to drug discovery. LLM Experience: Experience with LLMs (fine-tuning, pretraining, continued pretraining, inference, RAG, and building multi-agent workflows using Llamaindex, Langchain, LangGraph, vector databases, etc.). Production-Grade Models: Significant expertise in building production-grade machine learning models in industry and/or More ❯

for Information Retrieval, Natural Language Processing and Generative AI to join our AI Experiences team. Our teams are working on exciting initiatives such as: Building and deploying RAG systems, curating data for model training and evaluation, building evaluation systems that facilitate rapid iteration, and understanding how users interact with our systems to identify directions for improvements. Designing tools More ❯

varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term … cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI innovation, where your work will directly shape how next-generation systems interact, reason, and assist. More ❯

varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term … cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI innovation, where your work will directly shape how next-generation systems interact, reason, and assist. More ❯

varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term … cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI innovation, where your work will directly shape how next-generation systems interact, reason, and assist. More ❯

GPT-4.1, o3 and o4-mini along with others from Anthropic and Google Gemini. This places us at the forefront of THE most advanced technological advancements of our generation We're spearheading an unprecedented shift in how the world's asset class is transacted, globally. Legal reasoning is a hard problem and requires some of the smartest and … experiment, and ship new features directly to customers to use Explore and implement advanced concepts such as multi-agent systems, retrieval-augmented generation (RAG), agentic architectures and next generation OCR pipelines Champion quality and reuse across the product and the codebase. Work across the business to ensure the features you develop have More ❯

teammates, and fueling your curiosity for the latest trends in LLMs, MLOps, and ML more broadly. The impact you will have: Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation Build, scale, and optimize customer data science workloads and apply best in class MLOps … in Databricks Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap What we look for: Experience building Generative AI applications, including RAG, agents, text2sql, fine-tuning, and deploying LLMs, with tools such as HuggingFace, Langchain, and OpenAI Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools More ❯

and US investors . Our founders have delivered cutting-edge AI at world-class research labs and high-growth technology companies. Now, operating in stealth, we apply next-generation agentic AI to overhaul mission-critical enterprise workflows that still depend on error-prone, manual processes. Our vision is to bring these high-value operations into the modern era … event buses (Kafka, Pulsar). Wrangle large, heterogeneous data sets —model, transform, and index multi-modal, multi-terabyte enterprise datasets for advanced AI workloads Develop enterprise-level next generation AI systems with the support of our AI specialists Ship complete customer features - from architecture and code to CI/CD, infra-as-code (Terraform), rollout, and user training. … contract. Thrive in an early-stage, high-ownership environment—prototype today, deploy tomorrow, iterate next week. Bonus Points Experience deploying or consuming LLM-powered services (OpenAI, open-source models, RAG, vector stores) can be a bonus. However, we consider many great candidates without previous AI experience. What we're offering: Base salary from £115,000 - £135,000. .. plus meaningful More ❯

and US investors . Our founders have delivered cutting-edge AI at world-class research labs and high-growth technology companies. Now, operating in stealth, we apply next-generation agentic AI to overhaul mission-critical enterprise workflows that still depend on error-prone, manual processes. Our vision is to bring these high-value operations into the modern era … event buses (Kafka, Pulsar). Wrangle large, heterogeneous data sets —model, transform, and index multi-modal, multi-terabyte enterprise datasets for advanced AI workloads Develop enterprise-level next generation AI systems with the support of our AI specialists Ship complete customer features - from architecture and code to CI/CD, infra-as-code (Terraform), rollout, and user training. … contract. Thrive in an early-stage, high-ownership environment—prototype today, deploy tomorrow, iterate next week. Bonus Points Experience deploying or consuming LLM-powered services (OpenAI, open-source models, RAG, vector stores) can be a bonus. However, we consider many great candidates without previous AI experience. What we're offering: Base salary from £115,000 - £135,000. .. plus meaningful More ❯