26 to 50 of 849 LLM Jobs in the UK

of machine learning principles, deep learning techniques and GenAI concepts such as prompt engineering, chain-of-thought reasoning, prompt chaining, Retrieval-Augmented Generation (RAG), custom-built agents. Familiarity with LLM and agentic frameworks like LangChain, PydanticAI, or similar. Proficiency in ML-Ops practices and tools; strong understanding of DevOps and CI/CD. Experience with cloud platforms, e.g. AWS (preferred More ❯

a customer call to debug an API 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. Familiarity with supply-chain, procurement, or manufacturing More ❯

and Lead Data Scientists, contributing to high-impact projects for enterprise clients across industries including finance, tech, energy, and public services. What You’ll Be Doing Building and deploying LLM and speech-to-text applications for client use cases Contributing to solution design, from modelling approaches through to evaluation and delivery Processing and structuring large-scale text and audio data More ❯

in programming languages: Experience with Python and SQL for data analysis, manipulation, and modeling. Basic understanding of machine learning: Familiarity with predictive modeling techniques and algorithms, in particular NLP, LLM's and Time Series Forecasting. Experience with data visualisation tools: Knowledge of tools like Tableau/Power BI, or similar to present data effectively. Strong analytical skills: Ability to interpret More ❯

in programming languages: Experience with Python and SQL for data analysis, manipulation, and modeling. Basic understanding of machine learning: Familiarity with predictive modeling techniques and algorithms, in particular NLP, LLM's and Time Series Forecasting. Experience with data visualisation tools: Knowledge of tools like Tableau/Power BI, or similar to present data effectively. Strong analytical skills: Ability to interpret More ❯

Provide guidance to more junior members of the team, while orchestrating the work of the entire team. Good to have experience applying GenAI techniques like prompt engineering, RAG, or LLM fine-tuning to solve business problems. What You'll Bring 5-7 years of consulting experience or relevant industry experience, with at least 1+ years at a project lead level. More ❯

certifications such as OSCP, GIAC (GWEB, GWAPT, GCSA), CISSP, or CSSLP. Experience working in SaaS, multi-tenant cloud environments. Knowledge of machine learning security (AI/ML model risks, LLM security best practices). Familiarity with attack surface management and threat intelligence. What do we offer? We value our people and offer a competitive salary along with company bonus Strong More ❯

Shops & Onsite Shop, Sports & Social Club and More Skills Required: Proficiency in Data Science techniques, including statistical models and ML algorithms. Expertise in NLP, with a keen understanding of LLM and RAG technologies. Strong development capabilities, particularly in Python. Experience with data exchange, processing, and storage frameworks (ETL, ESB, API, SQL, NoSQL, and Parquet). Comfort with Agile development methodologies. More ❯

providing insights and recommendations on platform strategy and execution. Proactively identifying, managing, and communicating platform level risks and issues. Define and implement best practices for AI/ML/LLM operations. Drive automation and cost efficiency across cloud resources. Ensure platform governance, compliance, security and data privacy. Lead Platform Proofs of Concept (PoCs) and evaluate emerging technologies. Champion collaboration across More ❯

test infrastructure that combines traditional CI/CD pipelines with AI-driven decision making for optimized test selection, parallel execution, and automated result analysis Lead technical strategy for implementing LLM-based approaches to test script generation, automated debugging, and intelligent test maintenance across our distributed systems Pioneer innovative quality practices that leverage AI for automated performance analysis, intelligent chaos engineering More ❯

containerized deployments. Manage backup and disaster recovery procedures for all critical systems. Collaborate with engineering teams to containerize services and fine-tune runtime performance. Evaluate and integrate AI/LLM tools to improve automation, diagnostics, and operational efficiency. Requirements 5+ years of DevOps or SRE experience in high-availability, real-time systems. Strong hands-on experience with AWS services (EC2 More ❯

ASP.NET/Razor/Blazor also helpful Using Visual Studio and/or Visual Studio Code, Git, SSMS, Azure portal Understanding data-science and AI concepts like ML and LLM Aware of the latest trends in technology and software engineering Working with management: Works effectively to achieve the goals of the team and department, consulting regularly with management line Keeps More ❯

5G O-RAN domain, contributing to the next generation of intelligent mobile network solutions. Responsibilities: Design, implement, and evaluate machine learning models with a focus on deep learning and LLM applications Develop and fine-tune models for application development in the 5G O-RAN domain Collaborate with developers and domain experts to integrate AI solutions into scalable systems Leverage Kubernetes More ❯

and engineering teams. Ability to assess data dependencies, business constraints, and success criteria to deliver AI solutions that meet user and business needs. Expertise in AI Solution Architecture, including LLM/SLM (Large Language Models/Small Language Models) deployment, fine-tuning, inference optimization, retrieval-augmented generation (RAG), API-based AI deployment and model orchestration. Strong knowledge of Cloud AI More ❯

problems with innovative approaches while balancing real-world practicality to deliver meaningful impact. Key Responsibilities Lead multiple data science projects from concept to deployment.? Architect and implement GenAI/LLM solutions (prompt engineering, fine-tuning, evaluation frameworks).? Write and review high-quality Python code for production-ready solutions.? Communicate complex analytical findings in a clear, business-relevant way to More ❯

understanding of data modelling, ETL processes, and relational databases Experience with big data technologies and cloud platforms, ideally Azure Exposure to embedding models, vector search, and scalable deployment of LLM-powered solutions Other information Company Benefits and Initiatives Include: 25 days annual leave in addition to bank holidays - increasing by one additional day after 6 years, up to a maximum More ❯

understanding of data modelling, ETL processes, and relational databases Experience with big data technologies and cloud platforms, ideally Azure Exposure to embedding models, vector search, and scalable deployment of LLM-powered solutions Other information Company Benefits and Initiatives Include: 25 days annual leave in addition to bank holidays - increasing by one additional day after 6 years, up to a maximum More ❯

understanding of data modelling, ETL processes, and relational databases Experience with big data technologies and cloud platforms, ideally Azure Exposure to embedding models, vector search, and scalable deployment of LLM-powered solutions Other information Company Benefits and Initiatives Include: 25 days annual leave in addition to bank holidays - increasing by one additional day after 6 years, up to a maximum More ❯

person consultancy, this is an opportunity to shape cutting-edge GenAI solutions and lead projects from strategy through to deployment. What You’ll Be Doing Designing, developing, and deploying LLM-driven solutions across speech-to-text, anonymisation, and KPI extraction Leading projects and small teams (3–5 people) across full lifecycle AI/ML delivery Owning client relationships and presenting More ❯

cases in the context of intelligent file protection and the broader cybersecurity landscape. Validate feasibility with stakeholders, ensuring solutions are viable without reliance on cloud-based AI inferencing or LLM endpoints. Gather and elicit model requirements from defined use cases to enable agile development, rapid feedback loops, and continuous iteration across the delivery lifecycle. Collaboration with Data Science and Engineering More ❯

guiding us to deliver impact how and where it mattersmost . Connect to your opportunity Key Responsibilities: Solution Architecture: Define and design end-to-end AI/ML/LLM solution architectures, encompassing data ingestion, processing, model training, deployment, and monitoring. Technical Leadership: Provide technical guidance and mentorship to AI project teams, ensuring the adoption of best practices and the More ❯

Docker, Infrastructure as Code(CloudFormation, Terraform), CI/CD (Jenkins,GitHub Actions), Observability(AWS, Grafana) Development tools: GitHub, Jira, Notion, ChatGPT,Gemini,LangChain, AI-native IDE's (Cursor, JetBrains), LLM-powered internal tools. WHAT WE OFFER YOU A front-row seat in a fast scaling, early stage startup. Working on cutting edge problems withbrand new technologies. Join a passionate and More ❯

the playing field and believe access to the law should be a basic utility in society. Our AI lawyer Lawrence is built on top of our own fine tuned LLM and recently passed the UK's bar exam equivalent. We're backed by some of the top US and UK VC funds including Google Ventures, Balderton Capital and TQ Ventures. More ❯

the playing field and believe access to the law should be a basic utility in society. Our AI lawyer Lawrence is built on top of our own fine tuned LLM and recently passed the UK's bar exam equivalent. We're backed by some of the top US and UK VC funds including Google Ventures, Balderton Capital and TQ Ventures. More ❯

or experience working closely with ML/AI teams. Exposure to incorporating LLMs into engineering workflows for production-ready applications, including prompt engineering and context management. Familiarity with multiple LLM providers (e.g. OpenAI, Anthropic, Google) and an understanding of their comparative strengths, trade-offs, and integration models. Familiarity with DevOps tools such as GitHub Actions, Azure DevOps, or Terraform. Understanding More ❯