11 of 11 Hugging Face Jobs in the Thames Valley

field (Master's a plus) Extensive experience in professional software development Strong Python skills and a track record of delivering maintainable, well-tested code Experience with LLM APIs (OpenAI, Hugging Face, Anthropic) or ML frameworks (PyTorch, TensorFlow) Solid understanding of CI/CD, Git, testing, and agile methodologies Hands-on experience with Linux, Docker, and containerized deployments Familiarity More ❯

Description: Strong programming skills in Python (preferred), with experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ More ❯

AI ● Contribute to innovation, creating reusable frameworks, prototypes, and thought leadership What we’re looking for: ● Strong expertise in Python and leading AI/ML/NLP libraries (e.g. Hugging Face Transformers, spaCy, NLTK) ● Hands-on experience with LLMs (GPT, Claude, Llama, Mistral) and GenAI/Agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) ● Proven track record designing scalable AI More ❯

Technical Expertise Expert-level Python programming with deep knowledge of PyTorch, TensorFlow, or JAX Proven experience with distributed computing environments and modern MLOps workflows Practical knowledge of LLM toolkits (Hugging Face ecosystem, training frameworks) Strong problem-solving abilities for complex model performance and infrastructure challenges Highly Valued Advanced degree (Master's/PhD) in Computer Science, Machine Learning More ❯

or Personalisation . Strong understanding of ML fundamentals and deep learning frameworks (e.g., PyTorch, TensorFlow, JAX). Hands-on experience with GenAI , including working with LLMs (e.g., OpenAI, Anthropic, HuggingFace models). Deep knowledge of MLOps, experimentation, and model evaluation techniques. Experience scaling ML platforms, pipelines, and tooling in cloud environments (e.g., AWS, GCP, Azure). Preferred: PhD or MS More ❯

familiarity with ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex). Experience working with LLM APIs (e.g. Hugging Face, OpenAI). Exposure to conversational AI platforms (Dialogflow, Lex, Rasa, etc.). Ability to work collaboratively in fast-paced, agile, and multidisciplinary environments. Excellent communication skills and More ❯

data services. Desirable: Experience with asynchronous python programming Experience with graph technologies (e.g., Kuzu, Neo4j, Apache AGE). Familiarity with embedding models (hosted or local): OpenAI, Cohere etc or HuggingFace models/sentence-transformers. Solid understanding of data modeling, warehousing, and performance optimization. Experience with messaging middleware + streaming (e.g. NATS Jetstream, Redis Streams, Apache Kafka or Pulsar etc.) Hands More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯

learning or transformer based architectures • Hands on experience building and maintaining Frontend applications - React, Typescript • Strong programming background in Python and or relevant frameworks such as TensorFlow, PyTorch or Hugging Face • Fluent in cloud native development, containerisation, orchestration (for example Docker or Kubernetes) and CI/CD • Exceptional problem solver with an entrepreneurial mindset who is comfortable with More ❯

commercial teams to bring ideas to life What they’re looking for: 1–3 years’ experience in applied ML/AI (or equivalent projects) Strong Python skills with PyTorch, Hugging Face or scikit-learn Experience experimenting with LLMs (fine-tuning, embeddings, prompt chaining etc.) A passion for turning messy real-world data into something powerful and production-ready More ❯

to monitoring models in production Strong understanding of neural networks, CNNs, RNNs, LSTMs, and transformers Experience building automated data pipelines Hands-on experience with LLM tooling and libraries (e.g., Hugging Face Transformers/PEFT, tokenisers, spaCy or similar) Experience shipping NLP systems: prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based services Great knowledge More ❯