76 to 100 of 312 Hugging Face Jobs in the UK

we're looking for 4-5 years relevant experience Proficiency in Python or similar programming languages Experience with GenAI tools (LangGraph, CrewAI, OpenAI APIs, Hugging Face) ML fundamentals and LLM expertise (prompt engineering, cost optimization) Cloud platforms (AWS/GCP/Azure) and infrastructure-as-code DevOps tooling More ❯

CD pipelines, containerization, and cloud deployment for large-scale models. Solid programming skills in Python and familiarity with machine learning frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and MLOps tools (e.g., MLflow, Kubeflow). Strong analytical and problem-solving skills, with an aptitude for translating complex theoretical research More ❯

Master’s degree in Artificial Intelligence, Computer Science, or a related field; a PhD is preferred. Expertise in Generative AI and large models (e.g., Hugging Face, OpenAI APIs). Experience with MLOps and LLMOps for scalable model deployment. Proficiency in Python and cloud-based data platforms (e.g., Databricks More ❯

React, TypeScript, Node.js Required skills & experience: 3–5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or Hugging Face Proven experience with LLMs, RAG, and deploying cloud-native AI on AWS Strong full-stack skills (React, TypeScript, Node.js) and API development More ❯

Master’s degree in Artificial Intelligence, Computer Science, or a related field; a PhD is preferred. Expertise in Generative AI and large models (e.g., Hugging Face, OpenAI APIs). Experience with MLOps and LLMOps for scalable model deployment. Proficiency in Python and cloud-based data platforms (e.g., Databricks More ❯

Master’s degree in Artificial Intelligence, Computer Science, or a related field; a PhD is preferred. Expertise in Generative AI and large models (e.g., Hugging Face, OpenAI APIs). Experience with MLOps and LLMOps for scalable model deployment. Proficiency in Python and cloud-based data platforms (e.g., Databricks More ❯

ideas and concepts effectively. Ability to work independently and collaboratively. Preferred Skills: Experience building scalable applications with LLMs, using frameworks such as LangChain, LlamaIndex, Hugging Face, etc. Depth of knowledge with RAG implementation and improvements. Seniority level Mid-Senior level Employment type Full-time Job function Engineering and More ❯

experience in software engineering (or strong portfolio/projects), ideally in Python. Exposure to AI/ML tools, APIs, or foundational models (e.g. OpenAI, Hugging Face, LangChain). Familiarity with cloud services (e.g. AWS, GCP, or Azure) and containerization (e.g. Docker). Interest in or experience with building More ❯

CD pipelines, containerization, and cloud deployment for large-scale models. Solid programming skills in Python and familiarity with machine learning frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and MLOps tools (e.g., Strong analytical and problem-solving skills, with an aptitude for translating complex theoretical research into practical applications. More ❯

cloud-native deployment in a large-scale distributed environment. Knowledge of large language models (LLMs) and accompanying toolsets (e.g., Langchain, Vector databases, open-source Hugging Face Models). Knowledge in Reinforcement Learning or Meta Learning. Published research in areas of Machine Learning, Deep Learning, or Reinforcement Learning at More ❯

cloud AI services, model deployment, monitoring, and CI/CD pipelines for ML models (MLOps best practices). Example Tools & Technologies: Frameworks & Libraries: LangChain, Hugging Face Transformers, PyTorch, TensorFlow, Scikit-learn Agentic AI Tools: OpenAI GPT models, Crew,AI, Cohere, Pinecone (for vector databases), AutoGPT Data Engineering & ML More ❯

with OOP, and data-validation libraries such as Pydantic. Deep familiarity with Python and its ecosystem for AI/ML, including libraries like PyTorch, Hugging Face Transformers, and scikit-learn. Experience with data manipulation using libraries such as Pandas and NumPy, and familiarity with parallelization or asynchronous programming. More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

Experience with OOP, and data-validation libraries such as Pydantic. Deep familiarity with Python and its ecosystem for AI/ML, including libraries likePyTorch, Hugging Face Transformers, andscikit-learn. Experience withdata manipulationusing libraries such asPandasandNumPy, and familiarity withparallelizationorasynchronous programming. Proficiency in Test-Driven Development (TDD) and an understanding … that help people thrive at UnderwriteMe: Entrepreneurial: Shows initiative and a proactive approach to identifying and seizing the right opportunities. Shows resilience in the face of challenges and maintains a bias for action. Curiosity: Exhibits a strong desire to learn and understand new concepts. Approaches problems with creativity and More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯