101 to 125 of 364 Hugging Face Jobs in the UK

Practical knowledge of AI/ML technologies and their applications, including understanding language models (LLMs), and experience with training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Good understanding of programming/scripting: (e.g., Python, Go) for customizing solutions, creating scripts, or automating tasks. Experience with AI relevant infrastructure, including Networking (InfiniBand and More ❯

Practical knowledge of AI/ML technologies and their applications, including understanding language models (LLMs), and experience with training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Good understanding of programming/scripting: (e.g., Python, Go) for customizing solutions, creating scripts, or automating tasks. Experience with AI relevant infrastructure, including Networking (InfiniBand and More ❯

d love to hear from you! Requirements Proficiency in at least one programming language. I.e Python, C#, JavaScript, Kotlin, Java, Go.. Experience with Gen AI tools (e.g LangGraph, CrewAI, Hugging Face, OpenAI APIs etc) Experience in building and optimising systems for performance, scalability, and reliability Understanding of ML fundamentals (training, evaluation, deployment) and LLM-specific challenges (prompt engineering More ❯

projects—from data exploration and model development to deployment and evaluation. Expert-level proficiency in Python and ML libraries such as Scikit-learn, XGBoost, TensorFlow, PyTorch, and/or Hugging Face. Experience working with large-scale datasets, cloud platforms (AWS/GCP), and ML Ops tools is a plus. Excellent communication skills and the ability to translate technical insights More ❯

projects—from data exploration and model development to deployment and evaluation. Expert-level proficiency in Python and ML libraries such as Scikit-learn, XGBoost, TensorFlow, PyTorch, and/or Hugging Face. Experience working with large-scale datasets, cloud platforms (AWS/GCP), and ML Ops tools is a plus. Excellent communication skills and the ability to translate technical insights More ❯

projects—from data exploration and model development to deployment and evaluation. Expert-level proficiency in Python and ML libraries such as Scikit-learn, XGBoost, TensorFlow, PyTorch, and/or Hugging Face. Experience working with large-scale datasets, cloud platforms (AWS/GCP), and ML Ops tools is a plus. Excellent communication skills and the ability to translate technical insights More ❯

projects—from data exploration and model development to deployment and evaluation. Expert-level proficiency in Python and ML libraries such as Scikit-learn, XGBoost, TensorFlow, PyTorch, and/or Hugging Face. Experience working with large-scale datasets, cloud platforms (AWS/GCP), and ML Ops tools is a plus. Excellent communication skills and the ability to translate technical insights More ❯

projects—from data exploration and model development to deployment and evaluation. Expert-level proficiency in Python and ML libraries such as Scikit-learn, XGBoost, TensorFlow, PyTorch, and/or Hugging Face. Experience working with large-scale datasets, cloud platforms (AWS/GCP), and ML Ops tools is a plus. Excellent communication skills and the ability to translate technical insights More ❯

Python (must), familiarity with Node.js, Go, or Rust is a plus • Proficient with PyTorch or TensorFlow • Deep understanding of transformer architectures, embeddings, and attention mechanisms • Experience with LangChain, Transformers (HuggingFace), or LlamaIndex • Working knowledge of LLM fine-tuning (LoRA, QLoRA, PEFT) and prompt engineering • Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Chroma) • Cloud experience on Azure, AWS, or More ❯

of relevant pipeline and processes. Work experience with working in Linux and Microsoft Azure. Nice to Have Experience with deep learning, machine learning and NLP frameworks such as PyTorch, HuggingFace Transformer, Scikit-learn. Experience with multiple cloud platforms such as AWS, Google Cloud Platform, Oracle, NVIDIA, or on-prem environments. Perks and Benefits Salary dependent on experience Package of attractive More ❯

tune those models eg. XGBoost, Deep Neural Networks, Transformers, ResNets, VAEs, GANs, Markov chains, etc. Experience using specialized machine learning libraries eg. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. Experience of using Cloud technologies eg. AWS, GCP or More ❯

science or equivalent. - 1+ years of experience in developing, deploying or optimizing ML models. Exceptional engineering skills in building, testing, and maintaining scalable distributed GPU training frameworks. Familiar with HuggingFace Transformers for vision-language modeling. - Hands-on experience in large-scale multimodal LLM and generative model training. Contributions to popular open-source LLM frameworks or research publications in top-tier More ❯

science or equivalent. - 1+ years of experience in developing, deploying or optimizing ML models. Exceptional engineering skills in building, testing, and maintaining scalable distributed GPU training frameworks. Familiar with HuggingFace Transformers for vision-language modeling. - Hands-on experience in large-scale multimodal LLM and generative model training. Contributions to popular open-source LLM frameworks or research publications in top-tier More ❯

Science, Data Science, Statistics, or related field 3-5 years experience in NLP subdomains like sentiment analysis or natural language understanding Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Hugging Face, etc.) Strong understanding of machine learning engineering and software development Experience with data preprocessing, feature engineering, and model evaluation Experience in financial services industry What's In More ❯

Science, Data Science, Statistics, or related field 3-5 years experience in NLP subdomains like sentiment analysis or natural language understanding Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Hugging Face, etc.) Strong understanding of machine learning engineering and software development Experience with data preprocessing, feature engineering, and model evaluation Experience in financial services industry What's In More ❯

Science, Data Science, Statistics, or related field 3-5 years experience in NLP subdomains like sentiment analysis or natural language understanding Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Hugging Face, etc.) Strong understanding of machine learning engineering and software development Experience with data preprocessing, feature engineering, and model evaluation Experience in financial services industry What's In More ❯

Science, Data Science, Statistics, or related field 3-5 years experience in NLP subdomains like sentiment analysis or natural language understanding Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Hugging Face, etc.) Strong understanding of machine learning engineering and software development Experience with data preprocessing, feature engineering, and model evaluation Experience in financial services industry What's In More ❯

a leadership role . Strong understanding of software architecture, design patterns, and cloud-native development (preferably AWS or GCP). Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face) and deploying models in production. Proficiency in building RESTful APIs, microservices, and working with asynchronous frameworks (e.g., FastAPI, asyncio). Familiarity with containerization (Docker, Kubernetes) and CI More ❯

Experience within a startup with a self-starter mindset. Proven track record with NLP applications and transformer-based models like BERT or GPT. Advanced proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. Interested? Apply below or More ❯

Experience within a startup with a self-starter mindset. Proven track record with NLP applications and transformer-based models like BERT or GPT. Advanced proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or More ❯

Experience within a startup with a self-starter mindset. Proven track record with NLP applications and transformer-based models like BERT or GPT. Advanced proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or More ❯

Experience within a startup with a self-starter mindset. Proven track record with NLP applications and transformer-based models like BERT or GPT. Advanced proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or More ❯

Experience within a startup with a self-starter mindset. Proven track record with NLP applications and transformer-based models like BERT or GPT. Advanced proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or More ❯

into projects. What Were Looking For: Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Hands-on experience with NLP frameworks such as Hugging Face or spaCy. Strong understanding of data handling, including SQL, NoSQL, and building data processing pipelines. Familiarity with cloud platforms like AWS, Azure, or Google Cloud. Excellent problem More ❯

and compliance. Help shape the data pipeline and MLOps practices for handling sensitive legal content securely. Required Experience: Solid experience with Python and ML/NLP libraries (e.g., spaCy, Hugging Face, TensorFlow/PyTorch). Experience building NLP or document analysis solutions, ideally for legal or compliance use cases. Strong understanding of legal language, structures, and workflows (e.g. More ❯