1 to 25 of 320 Hugging Face Jobs in England

preprocessing, and feature engineering. Proven experience building and deploying RAG systems and/or LLM-powered applications in production environments. Proficiency in Python and ML libraries such as PyTorch, Hugging Face Transformers , or TensorFlow. Experience with vector search tools (e.g., FAISS, Pinecone, Weaviate) and retrieval frameworks (e.g., LangChain, LlamaIndex). Hands-on experience with fine-tuning and distillation More ❯

preprocessing, and feature engineering. Proven experience building and deploying RAG systems and/or LLM-powered applications in production environments. Proficiency in Python and ML libraries such as PyTorch, Hugging Face Transformers, or TensorFlow. Experience with vector search tools (e.g., FAISS, Pinecone, Weaviate) and retrieval frameworks (e.g., LangChain, LlamaIndex). Hands-on experience with fine-tuning and distillation More ❯

on expertise building and deploying deep learning models (e.g., CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP More ❯

art algorithms and pipelines for efficient data processing, feature engineering, and data transformation tailored for LLM and GenAI applications. GenAI Application Development: Apply and integrate frameworks like LangChain and Hugging Face Transformers to build modular, scalable, and robust Generative AI data pipelines and applications. Prompt Engineering Application: Apply advanced prompt engineering techniques to optimize LLM performance for specific … Advanced degree in AI, statistics, mathematics, computer science, or a related field. Programming and Frameworks: Deep experience with Python, TensorFlow or PyTorch, and NLP libraries such as spaCy and Hugging Face. GenAI Tools: Practical experience with LangChain, Hugging Face Transformers, and embedding models for building GenAI applications. Prompt Engineering: Deep expertise in prompt engineering, including prompt tuning More ❯

and scalable AI solutions. Requirements Qualifications: Experience: 3-5 years of experience in AI/ML development, with a focus on working with Large Language Models (e.g., GPT, BERT, Hugging Face, etc.). Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field (or equivalent experience). Technical Skills: Proficiency More ❯

and scalable AI solutions. Requirements Qualifications: Experience: 3-5 years of experience in AI/ML development, with a focus on working with Large Language Models (e.g., GPT, BERT, Hugging Face, etc.). Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field (or equivalent experience). Technical Skills: Proficiency More ❯

/LoRA, Context embedding, Vector database technologies and Semantic Search techniques & tools. Proficiency in programming languages such as Python and experience with NLP libraries such as NLTK, spaCy, Transformers, Hugging Face, BERT and Gen AI frameworks like Llangchain. Llamaindex etc. Strong problem-solving skills and ability to handle complex NLP challenges. Excellent communication and collaboration skills, with the More ❯

database systems such as SQL, MongoDB Experience on general programming languages: Python, C++, Java, etc. Experience with deep learning, machine learning and NLP frameworks such as PyTorch (or TensorFlow), HuggingFace Transformer, Scikit-learn Experience with working in Linux A strong intuition for what makes products a joy to use Empathy for how different users will need different things out of More ❯

AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI More ❯

AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI More ❯

AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI More ❯

AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI More ❯

AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI More ❯

AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI More ❯

Gemini, Llama, Falcon, Mistral. Model performance and optimization: Fine-tuning and optimizing LLMs for quality, latency, sustainability, and cost. Programming and NLP tools: Advanced Python, frameworks like PyTorch, TensorFlow, Hugging Face, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. Databases and data platforms: SQL, NoSQL More ❯

and Data cloud solutions. Experience working with Azure AI services (or AWS, GCP) and AI model deployment. Understanding of generative AI, LLMs, NLP, and machine learning frameworks (TensorFlow, PyTorch, Hugging Face, etc.). Understanding of the AI application lifecycle, including application prototyping, productionising and monitoring. Python/Go/R. Problem solving skills. Strong written and verbal communication More ❯

and Data cloud solutions. Experience working with Azure AI services (or AWS, GCP) and AI model deployment. Understanding of generative AI, LLMs, NLP, and machine learning frameworks (TensorFlow, PyTorch, Hugging Face, etc.). Understanding of the AI application lifecycle, including application prototyping, productionising and monitoring. Python/Go/R. Problem solving skills. Strong written and verbal communication More ❯

engineering. Demonstrated experience working closely with business stakeholders in R&D, translating complex scientific challenges into AI solutions. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face). Experience building and deploying models in cloud environments (e.g. Azure, GCP). Solid understanding of statistics, optimization, and experimental design. Preferred Qualifications & Skills: Please note the More ❯

data lake architectures, data integration, and data governance, and at least 2 years of experience with cloud-based AI/ML technologies (such as tools from AWS, Azure, Google, HuggingFace, OpenAI and Databricks) building ML or applied AI solutions. • A passion for Generative AI, and an understanding of strengths and weaknesses of Generative LLM's • Fundamental knowledge of ML, and More ❯

Computer Science, Applied Maths, Computational Linguistics, or related fields (MSc/PhD preferred). Experience with computational linguistics is highly desirable. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, Scikit-learn. Experience deploying AI solutions using AWS, GCP, or Azure. Hands-on experience with MLOps, CI/CD, and model performance monitoring. Background in More ❯

strongly preferred). Any candidates 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, CI/CD for ML More ❯

strongly preferred). Any candidates 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, CI/CD for ML More ❯

related fields (MSc/PhD preferred). Exposure to computational linguistics is highly desirable, from both academic research and commercial perspectives. 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, or Azure. Hands-on experience with MLOps, CI/CD for ML More ❯

grasp of CRM systems and finance/savings data (transaction flows, compliance, user segmentation, etc.) Technical Skills: Proficient in Python, SQL, and data science libraries (Pandas, NumPy, Scikit-learn, Hugging Face Transformers) Familiarity with embedding models, vector databases (e.g., Pinecone, FAISS, Weaviate) Experience with cloud platforms (AWS, GCP, or Azure) and MLOps pipelines Solid understanding of NLP, LLM More ❯

recognition systems that are deployed to production environments Must have solid programming skills in Python, along with experience in using relevant tools and frameworks such as PyTorch, FastAPI and Huggingface; moderate programming skills in Java are a plus. Familiarity with ML Ops system design and working with ML platforms (preferably, AWS SageMaker) is a plus. Strong analytical and problem-solving More ❯