1 to 25 of 210 Permanent OpenAI Jobs in London

Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms More ❯

Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms More ❯

Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms More ❯

Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms More ❯

applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models. Language Model Development: Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Cloud Computing Expertise: Proven architect kind of experience in cloud computing, particularly with Azure Cloud Services. Technical Proficiency: Strong skills in UNIX/Linux More ❯

applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models. Language Model Development: Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Cloud Computing Expertise: Proven architect kind of experience in cloud computing, particularly with Azure Cloud Services. Technical Proficiency: Strong skills in UNIX/Linux More ❯

applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models. Language Model Development: Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Cloud Computing Expertise: Proven architect kind of experience in cloud computing, particularly with Azure Cloud Services. Technical Proficiency: Strong skills in UNIX/Linux More ❯

applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models. Language Model Development: Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Cloud Computing Expertise: Proven architect kind of experience in cloud computing, particularly with Azure Cloud Services. Technical Proficiency: Strong skills in UNIX/Linux More ❯

AI solutions. This role requires deep expertise in enterprise architecture, AI systems design, and cloud-native platforms (specifically Microsoft Azure, leveraging services like Azure AI Studio/Foundry, Azure OpenAI, Databricks). Collaborate with C-suite executives, Directors, Business & technology stakeholders, data scientists, and engineering teams to ensure that AI initiatives are scalable, secure, ethically sound, and aligned with Ecolab More ❯

solutions. This role demands deep expertise in enterprise architecture, AI systems design, and cloud-native platforms, specifically Microsoft Azure, leveraging services such as Azure AI Studio/Foundry, Azure OpenAI, and Databricks. You will collaborate closely with C-suite executives, Directors, business and technology stakeholders, data scientists, and engineering teams to ensure AI initiatives are scalable, secure, ethically sound, and More ❯

solutions. This role demands deep expertise in enterprise architecture, AI systems design, and cloud-native platforms, specifically Microsoft Azure, leveraging services such as Azure AI Studio/Foundry, Azure OpenAI, and Databricks. You will collaborate closely with C-suite executives, Directors, business and technology stakeholders, data scientists, and engineering teams to ensure AI initiatives are scalable, secure, ethically sound, and More ❯

strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle management of More ❯

strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle management of More ❯

strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle management of More ❯

strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle management of More ❯

strategy. Key Responsibilities * End-to-end development of AI/ML solutions. * MLOps practices: CI/CD, model monitoring, retraining. * Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). * Generative AI features: embeddings, RAG, AI agents. * Clean, testable code with modern engineering practices. * Align with enterprise architecture and governance. * Collaborate with architects and stakeholders. * Lifecycle management of More ❯

for data manipulation Experience using Git, Jupyter Notebooks, and collaborative environments Experience in computer vision, natural language processing (NLP), or generative AI applications Familiarity with LangChain, Hugging Face, or OpenAI APIs for working with LLMs Experience with data pipeline tools (e.g., Airflow, Step Functions) or data validation frameworks (e.g., Great Expectations) Reply is an Equal Opportunities Employer and committed to More ❯

We’re Looking For Proficiency in generative AI model development, LLMs, and prompt engineering. Strong hands-on experience with Azure cloud services (Azure ML, Azure AI, Cognitive Services, Azure OpenAI). Solid Python coding background with ML frameworks (TensorFlow, PyTorch). Familiarity with Git, Docker, CI/CD pipelines, and MLOps practices. Excellent collaboration and communication skills for cross-functional More ❯

new techniques in 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 More ❯

new techniques in 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 More ❯

and user experience. Develop and integrate agentic frameworks, RAG pipelines, and vector database architectures to support natural language and intelligent automation use cases. Fine-tune and customise LLMs (e.g. OpenAI, Anthropic, and other models) for specific business applications. Collaborate with engineering and data science teams to implement MLOps best practices — from deployment and monitoring to continuous iteration. Partner with commercial More ❯

and user experience. Develop and integrate agentic frameworks, RAG pipelines, and vector database architectures to support natural language and intelligent automation use cases. Fine-tune and customise LLMs (e.g. OpenAI, Anthropic, and other models) for specific business applications. Collaborate with engineering and data science teams to implement MLOps best practices — from deployment and monitoring to continuous iteration. Partner with commercial More ❯

and user experience. Develop and integrate agentic frameworks, RAG pipelines, and vector database architectures to support natural language and intelligent automation use cases. Fine-tune and customise LLMs (e.g. OpenAI, Anthropic, and other models) for specific business applications. Collaborate with engineering and data science teams to implement MLOps best practices — from deployment and monitoring to continuous iteration. Partner with commercial More ❯

and user experience. Develop and integrate agentic frameworks, RAG pipelines, and vector database architectures to support natural language and intelligent automation use cases. Fine-tune and customise LLMs (e.g. OpenAI, Anthropic, and other models) for specific business applications. Collaborate with engineering and data science teams to implement MLOps best practices — from deployment and monitoring to continuous iteration. Partner with commercial More ❯

management, enablement, or internal communications Knowledge of AI ethics, compliance frameworks, or responsible AI guidelines Experience designing and optimizing prompts for large language models or generative AI platforms (e.g., OpenAI, Google Gemini, Adobe Firefly), ideally including proprietary in-house models. Familiarity with change management frameworks to effectively manage transitions and drive adoption, a plus. What's In It for You More ❯