76 to 100 of 143 Retrieval-Augmented Generation Jobs in the City of London

Strong academic background : BSc, MSc or PhD in Computer Science or related STEM subjects from leading UK universities 3+ years of professional experience Strong experience working with LLMs and RAG pipelines Machine Learning expertise Fluency in Python and modern ML/AI frameworks Comfortable wearing multiple hats Experience in a start-up or fast-paced environment You care deeply about More ❯

Strong academic background : BSc, MSc or PhD in Computer Science or related STEM subjects from leading UK universities 3+ years of professional experience Strong experience working with LLMs and RAG pipelines Machine Learning expertise Fluency in Python and modern ML/AI frameworks Comfortable wearing multiple hats Experience in a start-up or fast-paced environment You care deeply about More ❯

deploy AI/ML systems that boost accuracy, speed, and user experience. Partner with domain experts to turn complex workflows into AI-driven automation . Leverage LLMs, LangChain, and RAG at scale. Ship quickly, iterate fast, and set the foundation for our engineering culture . Requirements 2+ years in AI/ML engineering or applied research. Proven track record of More ❯

Vision/NLP Strong Software Engineering skills (3 years+) Developed LLM architecture and deployed LLM applications Uptodate with current trends in AI Some experience with applying latest techniques like RAG architecture, GenAI, Parallel training etc The role is hybrid, with adhoc requirements to be on client premises (London) this could be between 1-3 days a week, so we would More ❯

Vision/NLP Strong Software Engineering skills (3 years+) Developed LLM architecture and deployed LLM applications Uptodate with current trends in AI Some experience with applying latest techniques like RAG architecture, GenAI, Parallel training etc The role is hybrid, with adhoc requirements to be on client premises (London) this could be between 1-3 days a week, so we would More ❯

of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle management of models. Pilot emerging technologies. Experience & Skills …/professional services experience is a plus. AI/ML frameworks: PyTorch, TensorFlow, LangChain. Cloud: Azure (preferred), AWS, GCP. MLOps: CI/CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: ETL, governance. Strong coding, communication, and collaboration skills. Strategic thinking, problem-solving, and stakeholder engagement. More ❯

of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle management of models. Pilot emerging technologies. Experience & Skills …/professional services experience is a plus. AI/ML frameworks: PyTorch, TensorFlow, LangChain. Cloud: Azure (preferred), AWS, GCP. MLOps: CI/CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: ETL, governance. Strong coding, communication, and collaboration skills. Strategic thinking, problem-solving, and stakeholder engagement. More ❯

of AI/ML solutions. * MLOps practices: CI/CD, model monitoring, retraining. * Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). * Generative AI features: embeddings, RAG, AI agents. * Clean, testable code with modern engineering practices. * Align with enterprise architecture and governance. * Collaborate with architects and stakeholders. * Lifecycle management of models. * Pilot emerging technologies. Experience & Skills …/professional services experience is a plus. * AI/ML frameworks: PyTorch, TensorFlow, LangChain. * Cloud: Azure (preferred), AWS, GCP. * MLOps: CI/CD, model lifecycle, monitoring. * Generative AI: LLMs, RAG, chat agents. * Data engineering alignment: ETL, governance. * Strong coding, communication, and collaboration skills. * Strategic thinking, problem-solving, and stakeholder engagement. In accordance with the Employment Agencies and Employment Businesses Regulations More ❯

semantic layers using dbt and Delta Live Tables to ensure consistency across analytics and AI use cases Enable Generative AI and ML workloads by designing pipelines for vector search, RAG, and feature engineering Implement secure access and governance controls including RBAC, SSO, token policies, and pseudonymisation frameworks Support batch and streaming data flows using technologies like Kafka, Airflow, and Terraform More ❯

distributed systems and AI research. You'll have 2+ years of professional experience in big tech or start-up Proficiency in Python Strong hands on expertise with LLMs and RAG Traditional ML experience Based in London and in office by default Looking to throw everything into a business from the early days This is an exciting opportunity to join a More ❯

distributed systems and AI research. You'll have 2+ years of professional experience in big tech or start-up Proficiency in Python Strong hands on expertise with LLMs and RAG Traditional ML experience Based in London and in office by default Looking to throw everything into a business from the early days This is an exciting opportunity to join a More ❯

considerations in deploying AI systems. Desirable: Experience with agentic AI frameworks (e.g. AutoGPT, CrewAI, LangGraph, ReAct). Background in conversational design, human-AI interaction, or reinforcement learning. Familiarity with RAG, vector databases, or simulation environments. More ❯

considerations in deploying AI systems. Desirable: Experience with agentic AI frameworks (e.g. AutoGPT, CrewAI, LangGraph, ReAct). Background in conversational design, human-AI interaction, or reinforcement learning. Familiarity with RAG, vector databases, or simulation environments. More ❯

Storage , Queues , and SQL/NoSQL databases to build scalable, event-driven systems. Design and optimise APIs that serve our mobile and web products, including partner integrations. Implement efficient RAG AI backend systems for introducing advanced LLM based features Collaborate with product managers, data engineers, and frontend developers to deliver new features end to end. Write clean, maintainable, and well More ❯

Storage , Queues , and SQL/NoSQL databases to build scalable, event-driven systems. Design and optimise APIs that serve our mobile and web products, including partner integrations. Implement efficient RAG AI backend systems for introducing advanced LLM based features Collaborate with product managers, data engineers, and frontend developers to deliver new features end to end. Write clean, maintainable, and well More ❯

/day (negotiable) About the Role: We are seeking a Senior Gen AI Engineer to develop and deploy advanced Generative AI products, including fine-tuning LLMs and implementing Graph RAG solutions. You will implement and optimize Gen AI agents for the Global Supply Chain, delivering scalable, secure, and cost-effective AI solutions. Key Responsibilities: Prototype and deploy Generative AI applications … for business objectives. Implement LLMs, Graph RAG, and AI/ML solutions in production environments. Develop automated processes (LLMOps) and CI/CD pipelines. Collaborate with cross-functional teams to integrate AI into business workflows. Ensure security, compliance, and AI governance standards. Educate IT and business teams on Gen AI capabilities. Required Experience & Skills: Higher degree (PhD preferred) in CS … Statistics, Physics, Bioinformatics, or related field. 5+ years of hands-on experience across AI domains: NLP, NLG, CV, ML, GenAI. Expertise in fine-tuning/training LLMs and Graph RAG solutions in production. Proficiency in cloud services and tools: Azure, Databricks, Azure ML, Vertex AI, Azure AI Services, Azure DevOps. Strong Python and LLM libraries experience: langchain, LangGraph, semantic kernel More ❯

/day (negotiable) About the Role: We are seeking a Senior Gen AI Engineer to develop and deploy advanced Generative AI products, including fine-tuning LLMs and implementing Graph RAG solutions. You will implement and optimize Gen AI agents for the Global Supply Chain, delivering scalable, secure, and cost-effective AI solutions. Key Responsibilities: Prototype and deploy Generative AI applications … for business objectives. Implement LLMs, Graph RAG, and AI/ML solutions in production environments. Develop automated processes (LLMOps) and CI/CD pipelines. Collaborate with cross-functional teams to integrate AI into business workflows. Ensure security, compliance, and AI governance standards. Educate IT and business teams on Gen AI capabilities. Required Experience & Skills: Higher degree (PhD preferred) in CS … Statistics, Physics, Bioinformatics, or related field. 5+ years of hands-on experience across AI domains: NLP, NLG, CV, ML, GenAI. Expertise in fine-tuning/training LLMs and Graph RAG solutions in production. Proficiency in cloud services and tools: Azure, Databricks, Azure ML, Vertex AI, Azure AI Services, Azure DevOps. Strong Python and LLM libraries experience: langchain, LangGraph, semantic kernel More ❯

/day (negotiable) About the Role: We are seeking a Senior Gen AI Engineer to develop and deploy advanced Generative AI products, including fine-tuning LLMs and implementing Graph RAG solutions. You will implement and optimize Gen AI agents for the Global Supply Chain, delivering scalable, secure, and cost-effective AI solutions. Key Responsibilities: Prototype and deploy Generative AI applications … for business objectives. Implement LLMs, Graph RAG, and AI/ML solutions in production environments. Develop automated processes (LLMOps) and CI/CD pipelines. Collaborate with cross-functional teams to integrate AI into business workflows. Ensure security, compliance, and AI governance standards. Educate IT and business teams on Gen AI capabilities. Required Experience & Skills: Higher degree (PhD preferred) in CS … Statistics, Physics, Bioinformatics, or related field. 5+ years of hands-on experience across AI domains: NLP, NLG, CV, ML, GenAI. Expertise in fine-tuning/training LLMs and Graph RAG solutions in production. Proficiency in cloud services and tools: Azure, Databricks, Azure ML, Vertex AI, Azure AI Services, Azure DevOps. Strong Python and LLM libraries experience: langchain, LangGraph, semantic kernel More ❯

ML systems Deep knowledge of LLM architectures and attention mechanisms – experienced with MoE, MHA, SWA, Flash Attention, GPT, LLaMA, DeepSeek, and reasoning-based models Experience in creating and maintaining RAG supported systems including PDF extraction, OCR, and varying chunking and embedding methodologies Inference optimisation experience – hands-on with high-performance inference frameworks such as vLLM, TensorRT, and related acceleration techniques … Proven evaluation experience – successfully conducted assessments of RAG and agentic systems. Both on performance and compliance (harm, guardrails, etc) 4+ years of development competency across a variety of languages, frameworks, and tooling, such as Python, R, Kubernetes, Kubeflow, JavaScript/JVM, Kafka Background in Application development, deployment, and monitoring on Kubernetes Proficient in PyTorch or similar frameworks (e.g Tensorflow) – demonstrates More ❯

ML systems Deep knowledge of LLM architectures and attention mechanisms – experienced with MoE, MHA, SWA, Flash Attention, GPT, LLaMA, DeepSeek, and reasoning-based models Experience in creating and maintaining RAG supported systems including PDF extraction, OCR, and varying chunking and embedding methodologies Inference optimisation experience – hands-on with high-performance inference frameworks such as vLLM, TensorRT, and related acceleration techniques … Proven evaluation experience – successfully conducted assessments of RAG and agentic systems. Both on performance and compliance (harm, guardrails, etc) 4+ years of development competency across a variety of languages, frameworks, and tooling, such as Python, R, Kubernetes, Kubeflow, JavaScript/JVM, Kafka Background in Application development, deployment, and monitoring on Kubernetes Proficient in PyTorch or similar frameworks (e.g Tensorflow) – demonstrates More ❯

production-grade code shipping. Applied LLMs - Experience deploying multimodal foundation model-based products. Deep knowledge of LLM research, agents, tools, and function calling. Deploying LLMs - Experience with LangChain, indexing, RAG, semantic search, and fine-tuning (SFT/RL) of LLMs/agents. Why Join £100,000 – £170,000 base salary + meaningful equity Visa sponsorship and relocation support available A More ❯

production-grade code shipping. Applied LLMs - Experience deploying multimodal foundation model-based products. Deep knowledge of LLM research, agents, tools, and function calling. Deploying LLMs - Experience with LangChain, indexing, RAG, semantic search, and fine-tuning (SFT/RL) of LLMs/agents. Why Join £100,000 – £170,000 base salary + meaningful equity Visa sponsorship and relocation support available A More ❯

more about our culture on Role Summary We are seeking a Copyright Attorney to join our Legal team, focusing on data and content acquisitions for pre-training, post-training, RAG, and other AI applications. This is a new role, designed to provide legal support for the increasing number of licensing, data access, and partnership deals that fuel Mistral's AI More ❯

Lead AI Engineer/Consultant - Greenfield Outside IR35 £600 - £750pd flexible for the right person RAG experience a must. About the Company Market leading SaaS organisation building out their AI function. About the Role This project is a greenfield build out of AI capabilities. They are starting with RAG use cases as a low bar, but are targeting a rich … deliver an AI capability. Lead design, architecture, and delivery of advanced AI/ML and generative AI solutions, ensuring scalable, secure, and production-ready system. Expert in MCP and RAG patterns. Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow). Hands … complex, data-rich environments. Skilled in setting team engineering practices: Git, CI/CD, automated testing for ML code, code reviews, and documentation. Preferred Skills Expert in MCP and RAG patterns . Experience in developing agentic AI systems Lead tech enablement and mentor engineers, fostering culture of reliability, continuous improvement, and collaboration. Excellent communication skills, able to translate technical strategy More ❯

Lead AI Engineer/Consultant - Greenfield Outside IR35 600 - 750pd flexible for the right person RAG experience a must. About the Company Market leading SaaS organisation building out their AI function. About the Role This project is a greenfield build out of AI capabilities. They are starting with RAG use cases as a low bar, but are targeting a rich … deliver an AI capability. Lead design, architecture, and delivery of advanced AI/ML and generative AI solutions, ensuring scalable, secure, and production-ready system. Expert in MCP and RAG patterns. Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow). Hands … complex, data-rich environments. Skilled in setting team engineering practices: Git, CI/CD, automated testing for ML code, code reviews, and documentation. Preferred Skills Expert in MCP and RAG patterns . Experience in developing agentic AI systems Lead tech enablement and mentor engineers, fostering culture of reliability, continuous improvement, and collaboration. Excellent communication skills, able to translate technical strategy More ❯