826 to 850 of 2,242 LLM Jobs in London

focus on deploying and optimising speech and language models across cloud and edge environments. The successful candidate will work on production-grade ASR, TTS, LLM and Small Language Model pipelines , taking AI capabilities from development through to highly available, low-latency production environments. The Role As a Machine Learning Engineer … supporting real-time conversational applications. Key responsibilities will include: Designing and deploying production-grade, low-latency Automatic Speech Recognition (ASR), Text-to-Speech (TTS), LLM and Small Language Model (SLM) pipelines. Building high-performance asynchronous REST and WebSocket APIs using FastAPI to support real-time conversational AI applications. Deploying machine ...

landscape; with preference for GCP and Vercel , or suitable equivalents on AWS and Azure, and the capability to draw parallels across platforms. GEO and LLM optimisation: experience designing intelligent experiences and content structures optimised for generative engine discovery and LLM retrieval. Model fine‐tuning: experience customising and fine‐tuning existing ...

team can maintain after your engagement ends. What We're Looking For Significant professional software engineering experience (typically 6+ years), including several years building LLM-based or agentic systems, with a demonstrable track record as a senior or lead engineer. Strong software engineering fundamentals: you write clean, tested, production-grade … systems in production, owning them as an engineer rather than integrating them as a user. Strong Python, with hands-on experience building on LLM frameworks (LangGraph, LangChain, Haystack, or similar) and the ability to work below the framework when you need to. Experience designing and deploying AI/ML systems ...

landscape; with preference for GCP and Vercel, or suitable equivalents on AWS and Azure, and the capability to draw parallels across platforms.GEO and LLM optimisation: experience designing intelligent experiences and content structures optimised for generative engine discovery and LLM retrieval.Model fine-tuning: experience customising and fine-tuning existing models ...

based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and confidentiality.Key ResponsibilitiesML & LLM Engineering, Search and Recommendation EnginesAutomate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI … implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization Stay current with the latest ...

DevOps and MLOps practices, including large, distributed workloads, batch and streaming pipelines, and the data foundations that power machine learning, Generative AI and Large Language Model solutions. Working with architects, technology consultants and public sector client stakeholders, you will help customers make use of the data available to them while … languagesApproach solving problems pragmatically, creating clarity and structure in ambiguous situationsExperience productionising and operating data and AI/ML solutions, including Generative AI or LLM-based applicationsExperience coaching and mentoring engineers, putting in place structured development opportunities to build the capability of junior team members and client counterpartsYou will ...

opportunities that deliver measurable value. * Develop AI agents, automations and intelligent workflows across modern enterprise platforms. * Prototype and experiment with generative AI and large language model solutions. * Design and run pilot programmes with business users. * Measure outcomes, track benefits, and evaluate success against defined objectives. * Rapidly iterate solutions based … solutions, prototypes, automations or intelligent agents. * Strong understanding of AI technologies and their practical business applications. * Experience working with modern AI platforms and large language model technologies. * Ability to work independently and deliver outcomes in ambiguous environments. * Strong analytical and problem-solving capabilities. * Comfortable engaging with both technical ...

grade applications Experience designing and building AI, machine learning, generative AI, or agentic applications, including integration with enterprise systems and workflows Strong understanding of LLM application patterns, including prompt engineering, retrieval‐augmented generation, tool calling, context management, evaluation, and guardrails Experience with RESTful API design, development, and integration, including frameworks … across multidisciplinary teams Preferred Qualifications, Capabilities, and Skills Experience designing or operating multi‐agent systems, agent orchestration frameworks, workflow automation platforms, or tool‐augmented LLM applications Experience with context engineering techniques, including retrieval strategies, embeddings, vector databases, knowledge graphs, semantic search, memory management, and grounding approaches Experience building evaluation frameworks ...

causes, and provide actionable recommendations. Build scalable backend services and data-processing pipelines supporting device, account, fleet, and release-level diagnostics. Develop AI/LLM-powered diagnostic workflows that combine telemetry evidence, device events, and operational data. Build data correlation capabilities across devices, accounts, network signals, and software releases … skills, with the ability to work effectively across technical and cross-functional teams. Desirable skills and experience – Experience building or integrating Generative AI/LLM-based applications, including prompt engineering, model integration, structured outputs, RAG, or AI workflows. Experience with AWS, Docker, Kubernetes, and CI/CD technologies. Experience with ...

experiment, build and iterate yourself rather than write requirements for someone else to deliver. What you'll be doing Build AI agents, automations and LLM-powered prototypes against real business use cases. Prototype using AWS Bedrock and other emerging AI platforms and frameworks. Design and refine prompts, agent instructions … experience across a combination of: Generative AI, LLMs and Agentic AI Building AI agents/agentic workflows AWS Bedrock, Azure OpenAI or comparable enterprise LLM platforms Agent frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI or similar RAG, tool/function calling and grounding LLMs against enterprise data Prompt ...

Company DescriptionAt IFS, we're building the next generation of AI-native enterprise software, transforming how some of the world's largest organisations manage assets, operations and critical services. This is an opportunity to work ...

that accelerate experimentation and deployment for all model teams Ensure ML services are modular, testable, and monitored from day one Exploration and productionization of LLM-based features (e.g., retrieval pipelines, prompt evaluation, model serving) What we’re looking for Proven experience designing and deploying ML systems in production (5+ years … validation, deployment, and monitoring Ability to work independently with ML Scientists and mentor peers in reliability, testing, and delivery. Product impact driven. Exposure to LLM serving, vector databases, or GenAI-powered product flows Deep, hands‐on expertise in AI tools, especially in agentic AI SDLC Why you’ll love ...

need to have designed enterprise-scale agentic systems end-to-end, but you must have meaningful hands-on experience with the core components: LLM-powered applications, RAG architectures, agent frameworks, and enterprise platform integration. You are intellectually curious, technically rigorous, and energised by working at the frontier of what … ensuring the overall technical approach is sound, scalable, and aligned to client constraints. Designing and documenting agentic AI solution architectures — including multi-agent patterns, LLM-powered applications, retrieval-augmented generation (RAG) systems, and orchestration pipelines applied to commerce use cases such as personalisation, conversational commerce, intelligent search, and merchandising optimisation ...

Our client is a global credit ratings and risk analytics firm. We unite the brightest minds to turn today's risks into tomorrow's opportunities. We do this by striving to create an inclusive environment ...

Our client is a global credit ratings and risk analytics firm. We unite the brightest minds to turn todays risks into tomorrows opportunities. We do this by striving to create an inclusive environment where everyone ...

that combine deterministic, rules-based processing with agent-based reasoning in the same architecture Solid Python and SQL skills, and hands‐on experience with LLM or agent frameworks (LangChain or similar) Understanding of identity and authorisation models extended to non‐human/agent principals - delegated authority, composite human‐plus-agent … with persona‐or‐scenario‐based simulation for testing agent behaviour before release Familiarity with hybrid deterministic/agentic execution models, where rules-based and LLM-based reasoning share the same runtime Experience with token, spend, or step‐budget governance for autonomous agents operating at scale Understanding of security and privacy ...

Impact you will have Architecting Workloads: Design and implement production-level ML and AI workloads, including end-to-end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud-native services. GenAI Leadership ...

integration and prompt engineering to contributing to the technical direction for how we ingest, transform, store, serve, and govern the data that powers our LLM-based and agentic systems. You will build user-facing AI features that can be used in real-time, directly impacting how businesses plan and make … experience with a track record of delivering complex projects. Hands-on experience building and shipping AI/ML products in production. Practical experience with LLM-based systems: RAG architectures, embedding pipelines, prompt and response logging, and evaluation frameworks. Hands-on expertise with vector databases, graph databases, and knowledge graphs. ...

Senior Specialist Solutions Architect (AI/ML) London, United Kingdom Mission As a Senior Specialist Solutions Architect (ML & AI), you will serve as the trusted technical ML and AI expert for Databricks customers and the ...

integration and prompt engineering to contributing to the technical direction for how we ingest, transform, store, serve, and govern the data that powers our LLM-based and agentic systems. You will build user-facing AI features that can be used in real-time, directly impacting how businesses plan and make … experience with a track record of delivering complex projects. Hands-on experience building and shipping AI/ML products in production. Practical experience with LLM-based systems: RAG architectures, embedding pipelines, prompt and response logging, and evaluation frameworks. Hands-on expertise with vector databases, graph databases, and knowledge graphs. ...

About usAt Trainline, our purpose is to empower greener travel choices, connecting people and places. Trainline enables millions of travellers to find and book the best value tickets across carriers, fares, and journey options through ...

About us We are champions of rail, inspired to build a greener, more sustainable future of travel. Trainline enables millions of travellers to find and book the best value tickets across carriers, fares, and journey ...

Data Platform. We own the AI features that shape how buyers and sellers experience the marketplace, from agentic workflows in the customer journey to LLM-powered tooling for our dealer network. What we build goes into the hands of real sellers and thousands of verified dealers, usually within weeks. When …/CD, observability, and the MLOps practices that keep things healthy once they're live. You're hands-on across the GenAI stack: LLM APIs, retrieval and vector stores, agents with tool use, and structured outputs, running on cloud infrastructure (we use AWS and GCP). You have a real ...

AI EngineerLondon ( SE1) | Hybrid - 3 days on-site | 80,000 - 90,000 DOE + 5,000 car allowance + private medicalThe opportunityA prestigious household name UK consumer services business with tens of millions of operational ...

Role Overview Join the Alternatives Data Science team and lead data science and AI initiatives across the Real Estate investing platform. The role sits at the intersection of investing, AI, and analytics, partnering closely with ...