26 to 50 of 241 LLM Jobs in Central London

enterprise-grade AI/ML systems. Expertise with cloud AI stacks (AWS Bedrock, SageMaker, Azure OpenAI, Azure ML). Strong skills in Python, FastAPI, CI/CD, MLOps, and LLM orchestration. Leadership experience across multidisciplinary AI teams. Strategic mindset — able to bridge deep tech with business outcomes. Salary - £90,000 - 110,000 + bonus Working policy - 3 days onsite weekly More ❯

we’re looking for Experience in data analytics, data engineering, or campaign analytics. Strong SQL skills, plus Python (or R) for data processing and automation. Interest in AI/LLM applications — hands-on experience welcome but not essential. Understanding of digital performance metrics and data connectors (experience with platforms like Google Ads, Meta, or DSPs a bonus). Familiarity with More ❯

embed AI capabilities into wider systems. Translate emerging research into practical, deployable prototypes. What we’re looking for: Strong Python skills, with experience in PyTorch, TensorFlow, scikit-learn, and LLM frameworks Solid grounding in statistics, probability, and machine learning fundamentals. Experience with cloud (AWS/GCP/Azure), Docker, and API development What our client offers: Up to More ❯

a measurable impact. What you'll be doing: Collaborating with business teams to uncover and define AI/automation opportunities. Engineering and optimising prompts to ensure consistent, high-quality LLM outputs. Building and deploying AI-powered workflows that connect LLMs with business applications, APIs, and automation tools. Implementing RAG (Retrieval-Augmented Generation) pipelines to integrate enterprise data. Rapidly prototyping and More ❯

We are looking for: Experience supporting pre-sales activities in a consultancy or product-led environment Strong understanding of AI/ML techniques, such as reinforcement learning, planning algorithms, LLM-based agents, and simulation environments Proven experience in designing and developing agentic systems for production environments, including autonomous agents, multi-agent coordination, and decision- making frameworks Detailed knowledge of the More ❯

debate, align to unified decisions. Own operability: set up and maintain CI/CD, monitoring/alerting, performance & error budgets, and safe rollback paths. Build and integrate AI features (LLM/agent workflows, RAG/vector DB integration, eval hooks, cost/safety guardrails). Essential Requirements 3-6+ years building production backends/services , with shipped work and More ❯

growing FinTech in London who are building the next generation of AI based financial products. We are looking for Senior Software Engineers who have commercial experience with GenerativeAI and LLM integrations. You will be building Gen AI frontend agents and working with hybrid codebases with hosted prompts. This is a full stack opportunity working in their Gen AI team, working More ❯

Strong problem-solving skills; capable of delivering scalable, maintainable software. Effective communicator and team player. Knowledge of monitoring/alerting best practices for GenAI pipelines (e.g., Langsmith, Langfuse) and LLM-as-a-judge. Cloud experience (AWS, GCP) and familiarity with DevOps practices (CI/CD, Docker, Kubernetes, IaC). Experience with event-driven architecture and streaming (Kafka a strong plus More ❯

but operating as a tech lead in a flat structure. What they’re after: 5+ years’ experience building enterprise-grade software (Python, microservices, distributed systems) Proven track record deploying LLM-based applications Clear evidence of Software skills (CI/CD etc.) Ability to lead small teams, own solutions end-to-end, and mentor engineers Strong communicator with experience working in More ❯

Key Responsibilities Design and deliver AI & data strategies across portfolio companies and internal teams Lead technical diligence on AI-readiness and opportunities during deal evaluation Build and deploy reusable LLM/AI/ML systems (agents, copilots, etc.) to unlock value Define governance frameworks across risk, explainability, audit, and compliance Own internal AI transformation—deploying tools, platforms, and training programmes More ❯

Knowledge of financial data and systems (Bloomberg, SimCorp Dimension) preferred. Understanding of investment management workflows (portfolio management, risk, compliance, performance reporting). Experience with GitHub and AI tools (OpenAI, LLM APIs, agentic workflows). Qualifications: Bachelor’s degree in Computer Science, Quantitative Finance, Data Engineering/Analytics/Science, or related field. 2+ years of experience in data engineering, BI More ❯

and supporting delivery on key technical initiatives. Establish engineering best practices across performance, reliability, and security. Oversee the design and implementation of AI-driven systems — including multi-agent orchestration, LLM integration, and data pipelines (LangChain, LangSmith, vector databases). Drive continuous improvement in CI/CD, cloud infrastructure, and deployment processes (Docker, Kubernetes, AWS). Mentor engineers, recruit top talent More ❯

and backend services using Python, TypeScript, Go, Rust, or similar technologies. Design and ship backend systems from day one — scalable architectures, APIs, and AI-powered tools. Build and deploy LLM-based applications using frameworks such as LangChain, semantic search, RAG, and fine-tuning (SFT/RL). Develop backend logic and data pipelines to power intelligent automation and real-time More ❯

e.g. NumPy, Pandas), plus familiarity with deep learning tooling like PyTorch Expertise in a wide range of ML methods, including supervised and unsupervised learning, time series, or NLP and LLM/GenAI based projects. Ability to scope and structure solutions around ambiguous business problems, turning them into tractable pipelines Confident in managing small technical teams, reviewing work, and setting standards More ❯

understanding of cloud architecture. Exposure to UX/UI design and customer-focused development. Collaborative approach with a growth mindset and passion for problem-solving. Familiarity with AI/LLM technologies would be a bonus! The ideal candidate is someone who thrives in start-up environments where ideas move quickly, and impact is immediate. You’ll enjoy taking ownership, solving More ❯

to design and deliver scalable APIs, system components, and observability layers that enable extensibility and reuse. Collaborate with AI/ML teams to integrate capabilities such as semantic search, LLM-powered assistants, personalization, and classification systems. Write PRFAQs and technical narratives that align senior leadership, drive clarity across functions, and accelerate high-judgment decisions. Engage directly with CIOs, analysts, and More ❯

series forecasting, and anomaly detection. You need to know the concept and be handly with the most common libraries - Model Hosting and Monitoring: Host and monitor NLP models and LLM for real-time and batch inference. - Develop Monitoring Systems: Create and support robust models for monitoring. - Support and Innovate: Assist with a long tail of super important tasks, bringing innovative More ❯

and perform advanced searches with ElasticSearch. You’ll contribute to developing a cloud-native data platform that processes and indexes large-scale web data Refine search algorithms and explore LLM-based features You will play a key role in advancing their microservices-based, event-driven architecture. What you’ll bring: 3+ years of commercial software engineering experience with Python (FastAPI More ❯

through to production. What we’re looking for 3+ years of hands-on engineering experience in production environments. Strong Python skills. Experience with Generative AI : LLMs and RAG. Adapting LLM for use as a Q&A System. 👉 Apply now and help define the future of Defence AI. More ❯

will continuously collaborate across internal stakeholders to ensure the models being built are improving customer experience, and business efficiency. What we're looking for: Experienced ML Engineer, working across 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 More ❯

but operating as a tech lead in a flat structure. What they’re after: 5+ years’ experience building enterprise-grade software (Python, microservices, distributed systems) Proven track record deploying LLM-based applications Clear evidence of Software skills (CI/CD etc.) Ability to lead small teams, own solutions end-to-end, and mentor engineers Strong communicator with experience working in More ❯

client needs into technical solutions, requiring strong communication and stakeholder-facing capabilities. Leverage Generative AI Expertise Utilise your hands-on experience with generative AI tools or workflows, prompt engineering, LLM integration, or similar, but the emphasis is on engineering implementation and delivery. Who We're Looking For Essential Qualifications & Experience Strong software engineering background with deep experience deploying scalable systems More ❯

e.g. NumPy, Pandas), plus familiarity with deep learning tooling like PyTorch Expertise in a wide range of ML methods, including supervised and unsupervised learning, time series, or NLP and LLM/GenAI based projects. Ability to scope and structure solutions around ambiguous business problems, turning them into tractable pipelines Confident in managing small technical teams, reviewing work, and setting standards More ❯

make it repeatable, scalable, and delightful. What You'll Actually DoOwn Core Reporting Infrastructure (40%) Architect AI-powered reports: Design weekly email summaries, automated dashboards, and report templates using LLM summarization, structured extraction, and embedding-based clustering Craft intelligent prompts: Build and maintain the library of system prompts for ticket summarization, theme extraction, sentiment analysis, and qualitative insights Define reporting More ❯

chatbots, document summarization, code assistants, and more. Responsibilities: Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: Chatbots Document Q&A systems Report generators Code assistants Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy … in Python (preferred), with experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools More ❯