1 to 25 of 87 Hugging Face Jobs in the UK excluding London

years of experience in Machine Learning, Data Science, or NLP/LLM. Strong Python skills; exposure to PyTorch/TensorFlow/Hugging Face. (Bonus) understand fundamentals of deep learning, LLMs, and MLOps, vector databases, embeddings, or retrieval-augmented generation (RAG). Loves solving complex problems and thrives … senior ML engineers, AI researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, Hugging Face, OpenAI API, Pinecone, Kubernetes, etc.). Flexible working — remote-first culture with in-person team sessions for collaboration. Career acceleration — opportunities ...

experience building and deploying Agentic AI or multi-agent systems Proficiency in Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong … years. Profile 29 recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops ...

voice conversion etc.) Publications in relevant ML/AI/Signal Processing conferences or journals Experience with open-source toolkits such as SpeechBrain, ESPnet, Hugging Face, NeMo, Kaldi Experience deploying ML models to mobile platforms Knowledge of large-scale or distributed training pipelines Experience with cloud platforms ...

e.g., ICML, NeurIPS, ICLR, CVPR, SysML, INTERSPEECH, ICASSP, IEEE/ACM TASLP, IEEE TPAMI, JMLR). Experience with open-source speech processing toolkits (e.g., Hugging Face Transformers, SpeechBrain, ESPnet, Kaldi, NeMo). Experience developing and deploying AI models on Android mobile platforms. Proven experience in building and maintaining ...

Proficiency with cloud-native data platforms (AWS, Azure, GCP) and vector databases (Pinecone, Weaviate, Qdrant, or Chroma). Experience with MLOps tools and platforms (HuggingFace, SageMaker Bedrock, Vertex AI), experiment tracking (MLflow, Weights & Biases), and model deployment pipelines. Experience with Large Language Models (LLMs), embedding generation, retrieval-augmented generation ...

domain expertise required — curiosity and adaptability are key Technical skillset: Must-have: Python, data science/ML libraries (pandas, NumPy, scikit-learn, XGBoost, PyTorch, Hugging Face), experiment design, evaluation metrics Nice-to-have: LLM fine-tuning, prompt engineering, SQL/PostgreSQL How We Work We live ...

preferred). 5+ years' experience developing and deploying ML models in production environments. Strong Python skills, with experience in frameworks like PyTorch, TensorFlow, or Hugging Face. Confident working in AWS or similar cloud environments (SageMaker, Lambda, Docker, etc.). Experienced in (or eager to explore) areas such as forecasting ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...

using advanced Python techniques (monkey patching, decorators, introspection). ML Framework Integration: Build and maintain deep integrations with leading AI libraries (PyTorch, TensorFlow, Keras, Hugging Face, vLLM, scikit-learn). Packaging & Distribution: Manage the build lifecycle, creating and optimizing Python wheels and Eggs, and managing releases to PyPI ...