8 of 8 Semantic Kernel Jobs in the UK excluding London

and machine learning. Demonstrated proficiency in: Rapid prototyping of Data Science and Machine learning problems on large datasets. Building agentic workflows and autonomous agents using frameworks like Langchain, Semantic Kernel, AutoGen, and LangGraph. Developing and optimizing generative AI models, with a focus on prompt engineering and LLMs. Writing production-grade Python applications. Managing version control with More ❯

machine learning principles. Demonstrated proficiency in: Rapid prototyping of data science and machine learning solutions on large datasets. Building agentic workflows and autonomous agents using frameworks like Langchain, Semantic Kernel, AutoGen, and LangGraph. Developing and optimizing generative AI models, focusing on prompt engineering and LLMs. Writing production-grade Python applications. Managing version control with Git and More ❯

love you to have: Experience in AI/ML engineering or applied machine learning. Proven experience delivering production-grade AI solutions. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong understanding of data More ❯

practices across the organisation. Skills we would love you to have: Experience in AI/ML engineering or applied machine learning. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong understanding of data More ❯

to deliver real-world results What We’re Looking For • 5+ years' ML experience with strong Python skills • Experience with NLP, LLMs, and prompt engineering • Familiarity with LangChain, Semantic Kernel, or AutoGen • OCR/document layout modelling experience • Cloud-native deployment experience (AWS, Azure, or GCP) • Strong engineering mindset – writing production-grade, scalable code Bonus Points More ❯

science, or applied machine learning roles. Proven track record of delivering production-grade AI solutions in complex, data-rich environments. Proficiency in Python and key ML libraries (e.g., Semantic Kernel, Langchain, and Agentic frameworks). Experience deploying models into production using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong More ❯

science, or applied machine learning roles. Proven track record of delivering production-grade AI solutions in complex, data-rich environments. Proficiency in Python and key ML libraries (e.g. Semantic Kernel, Langchain and Agentic frameworks). Experience deploying models into production using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong More ❯

Visual Studio environment and embracing AI-assisted development. Comfortable working independently on AI-related features in a remote-first, async-friendly environment. Nice to Have: Experience with LangChain, Semantic Kernel , or similar orchestration frameworks. Familiarity with embedding models , vector stores, or retrieval-augmented generation (RAG). Contributions to open-source AI/dev tools or participation More ❯