51 to 75 of 408 Hugging Face Jobs

Computer Science, Machine Learning, or related field 3+ years of experience in machine learning or NLP, with significant hands-on experience with LLMs Proficiency with LLM frameworks such as Hugging Face Transformers, OpenAI API, LangChain, or similar Experience fine-tuning large transformer models or implementing retrieval-augmented generation systems Strong Python programming skills and familiarity with ML libraries More ❯

Demonstrate 4+ years of experience in data science, with a focus on NLP, Generative AI and LLMs. Proficiency in Python and experience working with LLMs and NLP frameworks (e.g. Hugging Face, Spacy, Pytorch/Tensorflow etc). Experience with Prompt Engineering, RAG techniques and various evaluation methodologies for integrating GenAI with search/retrieval systems and measure the More ❯

LLM such as GPT, LLaMA, Claude, or similar, including fine-tuning, prompt engineering, and deploying models in production environments. Strong proficiency in Python, with expertise in using frameworks like Hugging Face Transformers, LangChain, OpenAI APIs, or other LLM orchestration tools. A solid understanding of tokenisation, embedding models, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG More ❯

a Senior Data Scientist with proven experience leading AI projects and mentoring junior team members. You should have strong expertise in Python, including libraries such as TensorFlow, PyTorch, and Hugging Face Transformers, with a solid understanding of LLM architectures. You should be well-versed in various machine learning techniques, including supervised, unsupervised, and semi-supervised learning, as well More ❯

model explainability methods (SHAP, LIME) and adopt best practices for responsible AI. Qualifications Technical Skills Programming: Python (NumPy, Pandas), R, SQL. ML/DL Frameworks: Scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers. Big Data & Cloud: Databricks, Azure ML, AWS SageMaker, GCP Vertex AI. Automation: MLflow, Kubeflow, Weights & Biases for experiment tracking and deployment. Architectural Competencies Awareness of data More ❯

love to hear from you! Requirements Proficiency in at least one programming language (e.g., Python, C#, JavaScript, Kotlin, Java, Go). Experience with Gen AI tools (e.g., LangGraph, CrewAI, Hugging Face, OpenAI APIs) and ML frameworks such as PyTorch/TensorFlow. Experience in building and optimising systems for performance, scalability, and reliability. Strong understanding of ML fundamentals (training More ❯

fostering a learning culture within the team. Qualifications Experience managing data pipelines and leading a data science team. Proficiency in Python and experience with LLMs and NLP frameworks (e.g., Hugging Face, Spacy, Pytorch/Tensorflow). Knowledge of Prompt Engineering, RAG techniques, and evaluation methodologies for integrating GenAI with search/retrieval systems. Experience with LangChain/LlamaIndex More ❯

D problems that directly impact customers. OUR TECHNOLOGY STACK: Python • Agentic tools (Autogen, Semantic Kernel, LangChain) • SQL • MongoDB • Third-party LLM APIs • LiteLLM • MLflow • Google Cloud Platform • Docker • PyTorch • Hugging Face Transformers • SPARQL • Kubernetes WHAT YOU WILL BE DOING AT BEAMERY Join us at the forefront of transforming how organisations manage talent and plan their workforce. We're More ❯

define priorities and influence the product roadmap What we look for: Experience building Generative AI applications, including RAG, agents, text2sql, fine-tuning, and deploying LLMs, with tools such as HuggingFace, Langchain, and OpenAI Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch Experience building production-grade 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 ❯

pre-sales roles, or 4+ years in technical sales engineering with strong exposure to AI/LLM projects Proficiency with modern AI/LLM tools and frameworks (e.g. PyTorch, HuggingFace, OpenAI, Mistral, Llama, etc.) Strong Python skills and familiarity with cloud platforms, MLOps, and enterprise tech stacks Experience framing customer problems and delivering impactful AI solutions in real-world settings More ❯

how to fine-tune those 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 technologies eg. AWS, GCP or More ❯

Docker, orchestration with Kubernetes Experience deploying on AWS SageMaker, GCP Vertex AI, or Azure ML Proficient with MLflow, DVC, Kubeflow, Airflow, or Argo Workflows Tools & Frameworks: PyTorch, TensorFlow, Transformers (Hugging Face) LangChain, LlamaIndex, OpenAI API, FastAPI Git, Jenkins, Terraform (for infrastructure-as-code More ❯

or similar) Strong analytical skills and attention to detail Excellent communication skills and ability to explain complex AI concepts Preferred Qualifications Experience with AI frameworks like TensorFlow, PyTorch, or Hugging Face Background in developing multimodal AI solutions Knowledge of graph neural networks and their applications Experience with integrating various AI components into cohesive systems Familiarity with database systems More ❯

working relationships with cross-functional teams. Ability to clearly communicate and present to internal and external stakeholders. Nice to have, but not essential NLP/Deep learning experience (e.g. huggingface, spaCy) Deep learning framework experience (preferably PyTorch) MLOps experience (e.g. data and model versioning, model deployment CI/CD, MLFlow/DVC) Some basic devops experience useful (kubectl, helm, etc. … to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. Requisition ID: 7522 Reporting into: Director, Product, CX Role Type: Individual More ❯

LLM such as GPT, LLaMA, Claude, or similar, including fine-tuning, prompt engineering, and deploying models in production environments. Strong proficiency in Python, with expertise in using frameworks like Hugging Face Transformers, LangChain, OpenAI APIs, or other LLM orchestration tools. A solid understanding of tokenization, embedding models, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG More ❯

LLM such as GPT, LLaMA, Claude, or similar, including fine-tuning, prompt engineering, and deploying models in production environments. Strong proficiency in Python, with expertise in using frameworks like Hugging Face Transformers, LangChain, OpenAI APIs, or other LLM orchestration tools. A solid understanding of tokenization, embedding models, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG More ❯

LLM such as GPT, LLaMA, Claude, or similar, including fine-tuning, prompt engineering, and deploying models in production environments. Strong proficiency in Python, with expertise in using frameworks like Hugging Face Transformers, LangChain, OpenAI APIs, or other LLM orchestration tools. A solid understanding of tokenization, embedding models, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG More ❯

LLM such as GPT, LLaMA, Claude, or similar, including fine-tuning, prompt engineering, and deploying models in production environments. Strong proficiency in Python, with expertise in using frameworks like Hugging Face Transformers, LangChain, OpenAI APIs, or other LLM orchestration tools. A solid understanding of tokenization, embedding models, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG More ❯

systems. Additional skills include leadership in agile environments, strong communication, mentorship abilities, expertise in RAG architectures, Transformer-based LLMs, model optimization, programming in Python with frameworks like PyTorch, TensorFlow, Hugging Face, LangChain, experience with containerization tools, cloud deployment (preferably Azure), and familiarity with databases and data platforms. OUR VALUES: CURIOSITY, OPTIMISM, AMBITION, EMPATHY We foster a team culture More ❯

3+ years hands-on experience (predominantly industry gained) with LLMs (GPT, BERT, T5, Claude) and NLP frameworks Proficiency in prompt engineering, fine-tuning, and function-calling architectures Experience with Hugging Face, OpenAI APIs, and transformer libraries Understanding of model customization for domain-specific tasks Experience with retrieval-augmented generation (RAG) systems Knowledge of optimization techniques for reducing LLM More ❯

of experience in data science , with a focus on NLP , Generative AI and LLMs . Proficiency in Python and experience working with transformer based LLMs and NLP frameworks (e.g. Hugging Face, Spacy, Pytorch/Tensorflow etc ). Knowledge of Prompt Engineering , RAG techniques and various evaluation methodologies for integrating GenAI with search/retrieval systems and measure the More ❯

NoSQL databases (MongoDB, Cassandra, DynamoDB), message queueing systems (Kafka, RabbitMQ), and version control systems (Git). Preferred Skills: Experience with natural language processing libraries such as NLTK, spaCy, or Hugging Face Transformers. Familiarity with time-series databases and analysis tools. Knowledge of AI model serving frameworks like TensorFlow Serving or ONNX Runtime. Experience with AI ethics and bias More ❯

pipelines Working knowledge of embedding compliance and security in ML systems, including governance, access controls, and regulatory alignment (e.g., GDPR, HIPAA) Proficient with modern AI tooling and ecosystems, including Hugging Face, Cursor, vector DBs, and productivity tools that accelerate GenAI development Expertise in GenAI and LLMs, with hands-on experience in RAG solutions and agentic frameworks; capable of More ❯

also be considered People management experience: 1-3 years of people management experience Experience with scalable applications: Experience building scalable applications with LLMs, using frameworks such as LangChain, LlamaIndex, Hugging Face, etc. Depth of knowledge with RAG implementation: Expertise in RAG (Retrieval-Augmented Generation) implementation and improvements Benefits & perks (UK full-time employees): Generous PTO, plus company holidays More ❯