12 of 12 Hugging Face Jobs in the South East

/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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯