25 of 25 Permanent Hugging Face Jobs in the UK excluding London

/ML solutions. Responsibilities Collaborate across Data Science and DevOps to turn experimental ML models into deployed applications. Package and deploy ML models (including Hugging Face Transformers) as microservices on AWS. Build, train, and evaluate models using AWS tools like SageMaker, Bedrock, Glue, Athena, and Redshift. Develop secure … mindset. Enthusiastic about learning, adapting to new tools, and collaborating in a dynamic environment Tech Stack Languages & Frameworks: Python, R, SQL, Flask, FastAPI Tools: Hugging Face, Apigee, Jenkins, Git, RStudio, Jupyter Cloud: AWS (SageMaker, Glue, Athena, Redshift, Bedrock, ECS Fargate, Lambda) Please apply online for consideration. More ❯

hands-on experience in either academia or industry. Proficiency in Python and experience with ML/NLP libraries like TensorFlow, PyTorch, scikit-learn, or Hugging Face. Experience working with cloud platforms such as AWS, GCP, or Azure. Familiarity with advanced NLP methods, including Prompt Engineering, Parameter-Efficient Fine-Tuning More ❯

models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. 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 ❯

or ML Engineering roles Proven expertise deploying and scaling Generative AI models (GPT, Stable Diffusion, BERT) Proficiency with Python and ML frameworks (TensorFlow, PyTorch, Hugging Face) Strong cloud platform experience (AWS, GCP, Azure) and managed AI/ML services Practical experience with Docker, Kubernetes, and container orchestration Databricks More ❯

with exposure to computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps More ❯

with exposure to computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps More ❯

ML initiatives. Expertise in LLM-driven architectures, prompt engineering, and fine-tuning. Strong hands-on experience with AI frameworks like LangChain, OpenAI APIs, and Hugging Face. Deep understanding of multi-agent systems, decision-making algorithms, and reinforcement learning. Experience with cloud-based AI deployment (AWS, GCP, or Azure). More ❯

models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. 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 ❯

models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. 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 ❯

is required. Demonstrated ability in cybersecurity with a focus on artificial intelligence. Demonstrable experience with LLMs, deep understanding of AI/ML frameworks (PyTorch, Hugging Face, TensorFlow, etc.). Expertise in Python, knowledge of SQL a plus. Effective communication, interpersonal skills, and ability to work with partners across More ❯

the chatbot with existing financial systems and databases to deliver real-time, accurate insights. Experience: Hands-on development of LLM-based applications (OpenAI, Anthropic, Hugging Face, etc.). Strong Python programming skills, including libraries like pandas , numpy , and experience with data pipelines. Domain experience in finance (liquidity, risk More ❯

learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI innovation and a desire More ❯

practices for seamless model deployment, monitoring, and iteration. What We’re Looking For: 🔹 Strong Python skills – You know your way around TensorFlow, PyTorch, or Hugging Face. 🔹 Experience with LLMs, NLP, or recommendation algorithms . 🔹 Familiarity with MLOps, APIs, and scalable cloud solutions . 🔹 Passion for AI-powered personalisation and More ❯

include: Demonstrable experience designing and implementing machine learning models using Python frameworks such as TensorFlow or PyTorch Practical knowledge of generative AI tooling including Hugging Face transformers and LangChain orchestration Specialisation in natural language processing and large language models, covering training methodologies, deployment strategies and optimisation techniques Familiarity More ❯

Pinecone, ChromaDB, OpenSearch 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 ❯

experience with LLMs, vector databases, RAG pipelines, prompt engineering, and model fine-tuning Familiarity with cloud platforms (especially Azure), and tools such as Databricks, Hugging Face, LangChain, and open-source GenAI frameworks Deep curiosity and a passion for staying ahead of AI and data science developments Commercial acumen More ❯

Milvus, ChromaDB, or OpenSearch. Required skills & experience: 3-5+ years in machine learning and software development Proficient in Python, PyTorch or TensorFlow or Hugging Face Transformers Experience with RAG, LLM fine-tuning, and expertise in AWS and cloud-native AI deployments. Full-stack experience (React, TypeScript, Node.js More ❯

Milvus, ChromaDB, or OpenSearch. Required skills & experience: 3-5+ years in machine learning and software development Proficient in Python, PyTorch or TensorFlow or Hugging Face Transformers Experience with RAG, LLM fine-tuning, and expertise in AWS and cloud-native AI deployments. Full-stack experience (React, TypeScript, Node.js More ❯

NLP applications. Technical Skills: Knowledge of tools like Dialogflow, Microsoft Bot Framework, Rasa, and Amazon Lex. Knowledge with libraries such as spaCy, NLTK, and Hugging Face Transformers. Practical experience with Python, REST APIs, and dialog model training data preparation. Excellent ability to present complex AI concepts clearly and More ❯

RAG Expertise: Experience in Retrieval-Augmented Generation and related vector databases (e.g., Pinecone, FAISS, Weaviate). LLMs & NLP: Experience working with LLMs (OpenAI, Anthropic, Hugging Face, etc.), including model tuning, security, and optimization. Regulatory Knowledge: Understanding of AI governance, compliance frameworks, and security best practices. .NET Experience: Familiarity More ❯

equivalent experience in ML, NLP, or a related discipline, with strong understanding of LLM internals. Toolbelt Ready : Proficient in Python and LLM tools like Hugging Face, LangChain, or OpenAI API. Prompt-Savvy : Comfortable with prompt engineering, model evaluation, and structured analysis of generative systems. Experimentation First : Experience (or More ❯

Programming proficiency: Excellent Python programming skills with experience in developing and debugging production-level code. Bonus points: Deep learning frameworks: Expertise with PyTorch and HuggingFace transformers. Generative AI: Strong practical understanding of LLMs and transformers. PhD in a related field. Reinforcement Learning knowledge. 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 ❯

data science, with a strong preference for experience in the insurance or financial services sector. Experience working with LLMs and NLP frameworks such as Hugging Face or OpenAI is a strong advantage. Proven experience managing and mentoring a team of data professionals, with a commitment to fostering a More ❯

marketing to AI labs, GPU buyers, DevOps teams, or enterprise R&D Familiarity with cloud-native technologies, LLM infrastructure, or ecosystem players like NVIDIA, Hugging Face, or MLOps vendors Background in partner or channel marketing Working knowledge of SEO, SEM, and campaign analytics Benefits Competitive total compensation package More ❯