26 to 50 of 573 LLM Jobs in London

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 ❯

what is key is that you will be deeply involved with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle More ❯

what is key is that you will be deeply involved with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle More ❯

years of experience in designing, developing, deploying, and monitoring machine learning and GenAI solutions 2+ years of experience in Application development, deployment, and monitoring on Kubernetes Deep knowledge of LLM architectures and attention mechanisms Education: Bachelor’s/Master’s/PHD degree in any of the following: Engineering, statistics, machine learning, computational linguistics or relevant areas Commodity Trading Expertise More ❯

years of experience in designing, developing, deploying, and monitoring machine learning and GenAI solutions 2+ years of experience in Application development, deployment, and monitoring on Kubernetes Deep knowledge of LLM architectures and attention mechanisms Education: Bachelor’s/Master’s/PHD degree in any of the following: Engineering, statistics, machine learning, computational linguistics or relevant areas Commodity Trading Expertise More ❯

/PySpark/Databricks or distributed data experience Familiarity with AWS (S3, EMR) or Hive-based environments Consulting or enterprise B2B experience Exposure to causal AI, agentic systems, or LLM applications 💼 Why Join Join a multi-award-winning AI innovator operating at global scale Work on meaningful, high-impact AI projects with blue-chip clients Hybrid setup — 3 days per More ❯

collaboratively with the team to ensure project deadlines are met. Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for enterprise use cases. Build and fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. Integrate More ❯

agentic platform. Key Responsibilities Collaborate with client teams to understand domain challenges and success metrics. Translate business requirements into scalable AI solutions using the agentic framework. Prototype and deploy LLM-based agents (prompt structures, orchestration logic, memory, retrieval pipelines). Drive the transition from proof-of-concept to production with reliability and measurable ROI. Act as a trusted technical advisor More ❯

agentic platform. Key Responsibilities Collaborate with client teams to understand domain challenges and success metrics. Translate business requirements into scalable AI solutions using the agentic framework. Prototype and deploy LLM-based agents (prompt structures, orchestration logic, memory, retrieval pipelines). Drive the transition from proof-of-concept to production with reliability and measurable ROI. Act as a trusted technical advisor More ❯

experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and communicate results across cross-functional teams. Define, implement, and monitor key performance metrics for AI-driven product features. Stay up More ❯

experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and communicate results across cross-functional teams. Define, implement, and monitor key performance metrics for AI-driven product features. Stay up More ❯

ML Engineering and MLOps principles (cloud-based pipelines, CI/CD, monitoring, reproducibility). Experience with Python, SQL & Azure (AWS & GCP is also fine). Exposure to GenAI or LLM tools and frameworks is a strong advantage. Strategic thinker with the confidence to lead technically and shape the roadmap for ML within a growing, collaborative team. Desire to apply technology More ❯

ML Engineering and MLOps principles (cloud-based pipelines, CI/CD, monitoring, reproducibility). Experience with Python, SQL & Azure (AWS & GCP is also fine). Exposure to GenAI or LLM tools and frameworks is a strong advantage. Strategic thinker with the confidence to lead technically and shape the roadmap for ML within a growing, collaborative team. Desire to apply technology More ❯

native development. Python scripting proficiency at platform engineer level but an understanding of software development lifecycle and production system ownership. Interest or experience in GenAI infrastructure - RAG, vector databases, LLM platforms, or agent frameworks. Strong communication skills and ability to translate technical decisions into business outcomes. This role is NOT an ML Engineering position - you won't be training models More ❯

native development. Python scripting proficiency at platform engineer level but an understanding of software development lifecycle and production system ownership. Interest or experience in GenAI infrastructure - RAG, vector databases, LLM platforms, or agent frameworks. Strong communication skills and ability to translate technical decisions into business outcomes. This role is NOT an ML Engineering position - you won't be training models More ❯

impact solutions Job Responsibilities/Objectives Build and deploy Python based AI applications Research and design advanced experiments and prototypes using cutting edge techniques, specifically in GenAI Develop various LLM assisted frameworks Design and write clean, maintainable, auditable and well documented codebases Implement testing pipelines and evaluation frameworks Good documentation practices to ensure seamless operations Exceptional teamwork and communication skills More ❯

experience writing scalable, production-ready code. Hands-on experience with PyTorch, Transformer architectures, and Large Language Models (LLMs). Demonstrated success delivering Computer Vision and/or NLP/LLM projects into production. Solid understanding of model deployment, pipelines, and software development fundamentals. Expertise in Deep Learning, including training, evaluation, and optimisation. Strong grounding in mathematics, statistics, and data analysis. More ❯

in Python and familiarity with ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex). Experience working with LLM APIs (e.g. Hugging Face, OpenAI). Exposure to conversational AI platforms (Dialogflow, Lex, Rasa, etc.). Ability to work collaboratively in fast-paced, agile, and multidisciplinary environments. Excellent communication skills More ❯

in Python and familiarity with ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex). Experience working with LLM APIs (e.g. Hugging Face, OpenAI). Exposure to conversational AI platforms (Dialogflow, Lex, Rasa, etc.). Ability to work collaboratively in fast-paced, agile, and multidisciplinary environments. Excellent communication skills More ❯

modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

You’ll Do Define and implement the AI strategy, operating model, and governance structure . Architect and scale AI and ML platforms for enterprise-wide adoption. Lead deployment of LLM, RAG, and Generative AI systems at scale. Partner with business, data, and engineering teams to operationalize AI initiatives. Establish MLOps and LLMOps frameworks for lifecycle automation, compliance, and monitoring. Champion More ❯

models — while leading a small, high-performing team. What You’ll Do Build and maintain data pipelines and cloud infrastructure (AWS/GCP). Develop AI-driven applications including LLM tools, RAG pipelines, and automation solutions. Lead on client communication , project delivery, and stakeholder alignment. Collaborate with Data Science and Analytics teams to improve data access, automation, and governance. Drive More ❯

Experience delivering and scaling enterprise AI/ML systems Hands-on expertise with cloud AI platforms (AWS, Azure, etc.) Strong Python engineering skills + FastAPI, CI/CD, MLOps, LLM tooling Leadership across cross-functional engineering teams If you are Interested, apply directly or reach out to jonah.brookes@oliverbernard.com Principal AI Engineer | Up to £130K | Hybrid in London (3 Days More ❯

Experience delivering and scaling enterprise AI/ML systems Hands-on expertise with cloud AI platforms (AWS, Azure, etc.) Strong Python engineering skills + FastAPI, CI/CD, MLOps, LLM tooling Leadership across cross-functional engineering teams If you are Interested, apply directly or reach out to jonah.brookes@oliverbernard.com Principal AI Engineer | Up to £130K | Hybrid in London (3 Days More ❯