1 to 25 of 573 LLM Jobs in London

systems into the wider enterprise architecture. Technical Skillset Requirements Core AI & Frameworks: Agentic Frameworks: Expert-level knowledge of agentic frameworks such as LangChain, LangGraph, Google Agent Development Kit (ADK) LLM Expertise: Advanced Prompt Engineering and hands-on experience with model fine-tuning techniques including PEFT and QLoRA. Proven experience with models like Gemini, and Llama 3. RAG & Vector Databases: Deep More ❯

systems into the wider enterprise architecture. Technical Skillset Requirements Core AI & Frameworks: Agentic Frameworks: Expert-level knowledge of agentic frameworks such as LangChain, LangGraph, Google Agent Development Kit (ADK) LLM Expertise: Advanced Prompt Engineering and hands-on experience with model fine-tuning techniques including PEFT and QLoRA. Proven experience with models like Gemini, and Llama 3. RAG & Vector Databases: Deep More ❯

Infrastructure & cloud : Familiarity with cloud platforms (Azure preferred; AWS or GCP also valuable), containerization (Docker, Kubernetes), and infrastructure-as-code tools like Terraform. Applied AI development: Experience working with LLM APIs (e.g., OpenAI) and building lightweight AI agents. Familiarity with orchestration tools like Temporal is a plus. Collaboration and impact: Strong problem-solving ability, intellectual curiosity, and a pragmatic approach More ❯

Infrastructure & cloud : Familiarity with cloud platforms (Azure preferred; AWS or GCP also valuable), containerization (Docker, Kubernetes), and infrastructure-as-code tools like Terraform. Applied AI development: Experience working with LLM APIs (e.g., OpenAI) and building lightweight AI agents. Familiarity with orchestration tools like Temporal is a plus. Collaboration and impact: Strong problem-solving ability, intellectual curiosity, and a pragmatic approach More ❯

are proficient in developing data pipelines for large, complex datasets using Python, SQL, NoSQL, and big data tools, preferably on AWS or Azure. You have hands-on experience with LLM operations and agentic AI tools such as GPT-5, LangChain, and vector databases. You understand MLOps, including deployment, monitoring, and CI/CD pipelines, and can effectively communicate complex technical More ❯

Degree in Statistics, Computer Science, or a related field. - 5+ years in data science with at least 2 years leading teams. - Proven success in production deployment of ML/LLM/NLP/CV models. - Strong understanding of machine learning fundamentals, statistical inference, and model evaluation. - Advanced proficiency in SQL (e.g., PostgreSQL, ELT/ETL) and Python (PyTorch, LightGBM, Scikit More ❯

Degree in Statistics, Computer Science, or a related field. - 5+ years in data science with at least 2 years leading teams. - Proven success in production deployment of ML/LLM/NLP/CV models. - Strong understanding of machine learning fundamentals, statistical inference, and model evaluation. - Advanced proficiency in SQL (e.g., PostgreSQL, ELT/ETL) and Python (PyTorch, LightGBM, Scikit More ❯

ready applications that drive automation, optimisation, and intelligence across multiple industries. What You’ll Be Doing: Designing, developing, and deploying machine learning and AI models Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines More ❯

ready applications that drive automation, optimisation, and intelligence across multiple industries. What You’ll Be Doing: Designing, developing, and deploying machine learning and AI models Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines More ❯

AI orchestration and agentic reasoning What We’re Looking For Proven experience with LangGraph (bonus: contributions to the open-source project) Strong background in Python, LangChain, OpenAI APIs, and LLM architectures Familiarity with vector databases, retrieval-augmented generation (RAG), and prompt engineering Understanding of software design principles, version control (Git), and CI/CD practices Creative problem-solver with a More ❯

AI orchestration and agentic reasoning What We’re Looking For Proven experience with LangGraph (bonus: contributions to the open-source project) Strong background in Python, LangChain, OpenAI APIs, and LLM architectures Familiarity with vector databases, retrieval-augmented generation (RAG), and prompt engineering Understanding of software design principles, version control (Git), and CI/CD practices Creative problem-solver with a More ❯

Ensure your agents comply with regulations (GDPR, financial compliance) and guard against bias, hallucinations, and misuse. What You Bring Technical Mastery: Strong skills in Python, JavaScript, or similar languages. LLM & Agent Expertise: Hands-on experience with LLMs (OpenAI, Anthropic, Mistral) and agent frameworks. Advanced Tools: Familiarity with vector databases, RAG pipelines, prompt engineering, REST APIs, cloud deployment, and containerization (Docker More ❯

of API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and More ❯

of API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and More ❯

Azure/GCP), CI/CD, Docker/Kubernetes; workflow orchestration (Airflow/Prefect); experiment tracking (MLflow/W&B). Machine Learning for time series/tabular data; LLM/agentic systems, retrieval pipelines, and evaluation/guardrails. Research driven, rigorous and curious; clear scientific writing with a publication mindset. Ability to communicate complex ideas to non-technical audiences More ❯

of API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and More ❯

of API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and More ❯

Key Responsibilities Design, build, and deploy Python-based AI and ML applications . Research and develop new Generative AI techniques, including fine-tuning and prompt engineering. Develop and maintain LLM-assisted frameworks and automation pipelines. Write clean, maintainable, and well-documented code for scalable deployment. Build and implement testing and evaluation frameworks for AI models. Collaborate with data scientists, software More ❯

Deployment: Design, prototype, and deploy state-of-the-art Generative AI models (e.g., LLMs, Transformers, Diffusion models ) tailored for enterprise use cases. Application Development: Build, fine-tune, and deploy LLM-based applications such as advanced chatbots, summarization tools, document Q&A systems, and code assistants. Advanced Techniques: Apply sophisticated techniques like Prompt Engineering , Retrieval-Augmented Generation (RAG) , and context-aware More ❯

Deployment: Design, prototype, and deploy state-of-the-art Generative AI models (e.g., LLMs, Transformers, Diffusion models ) tailored for enterprise use cases. Application Development: Build, fine-tune, and deploy LLM-based applications such as advanced chatbots, summarization tools, document Q&A systems, and code assistants. Advanced Techniques: Apply sophisticated techniques like Prompt Engineering , Retrieval-Augmented Generation (RAG) , and context-aware More ❯

and drive student success. WHAT YOU WILL BE DOING: Design and develop AI-driven systems and tools that enhance the learning experience for students and educators. Build and deploy LLM-based solutions, integrating frameworks such as LangChain, AutoGen, and RAG pipelines. Develop and optimise AI agents capable of reasoning, planning, and automating complex learning or data workflows. Collaborate with cross More ❯

gRPC) and working with containerised environments (Docker, Kubernetes). Solid grasp of distributed systems, networking, and infrastructure-as-code practices. Familiarity with vector databases, retrieval-augmented generation (RAG), and LLM integration is a plus. Exposure to cloud platforms (AWS preferred) and messaging systems (Kafka, RabbitMQ) is advantageous. Strong communication skills and the ability to work across technical and non-technical More ❯

technical debt management Ability to establish coding standards and best practices across teams AI/ML Expertise Strong understanding of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) Experience with LLM integration (OpenAI, Anthropic, open-source models) Knowledge of RAG architectures, prompt engineering, and vector databases (Pinecone, Weaviate) Experience with MLOps tools and monitoring model performance in production Automation Architecture Deep More ❯

technical debt management Ability to establish coding standards and best practices across teams AI/ML Expertise Strong understanding of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) Experience with LLM integration (OpenAI, Anthropic, open-source models) Knowledge of RAG architectures, prompt engineering, and vector databases (Pinecone, Weaviate) Experience with MLOps tools and monitoring model performance in production Automation Architecture Deep More ❯

Foundry (full training provided). Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real-world consequences. Growth: Multiple openings from mid More ❯