51 to 75 of 1,122 LLM Jobs in England

the company. What we are looking for: Research engineering: Industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework. Cloud-native technologies: Experience in developing and deploying More ❯

technical discovery or architecture definition in a scaling SaaS or fintech environment. Familiarity with event-driven or streaming architectures (Kafka, Apache Flink, etc.). Practical exposure to AI/LLM orchestration frameworks or fine-tuning workflows. Experience designing developer tools, data platforms, or intelligent systems. Interest in or experience mentoring engineers in applied AI. Degree in Computer Science or related More ❯

looking for: Research engineering: 2-3 years of industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers More ❯

looking for: Research engineering: 2-3 years of industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers More ❯

looking for: Research engineering: 2-3 years of industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers More ❯

looking for: Research engineering: 2-3 years of industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 Carbon60, Lorien & SRG 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 ❯

such as credit decisioning, fraud detection, personalized banking, claims processing, underwriting automation, and algorithmic trading. Provide consulting on Gen-AI scalability, governance, prompt engineering, Gen-AI factory setup, and LLM fine-tuning. Integrate advanced AI technologies using platforms like OpenAI, Anthropic, Meta's LLaMA, and emerging multi-modal models. Design and deploy autonomous agentic AI systems for financial applications, including More ❯