8 of 8 Remote 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯