1 to 25 of 188 Remote Hugging Face Jobs

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 ❯

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 ❯

Machine Learning projects, following methodologies such as CRISP-DM. Design, implement, and optimize NLP (Natural Language Processing) and Generative AI models, using advanced frameworks such as PyTorch, TensorFlow, or Hugging Face. Collaborate with engineering teams to integrate models into production environments using MLOps practices and CI/CD pipelines. Analyze large volumes of structured and unstructured data using tools More ❯

generative models. Hands-on experience with LLMs such as OpenAI GPT, Anthropic Claude, Mistral, Cohere, or similar. Proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, or LangChain. Experience in fine-tuning, model evaluation, and prompt engineering. Strong understanding of NLP techniques including text classification, summarization, sentiment analysis, and dialogue systems. Experience 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 ❯

typical workflows in banking, asset management, or fintech. Experience with LLMs (e.g., GPT, LLaMA), prompt tuning, and embedding-based retrieval systems. Proficiency in Python and ML libraries (e.g., PyTorch, Hugging Face Transformers, LangChain). Familiarity with cloud platforms (AWS, GCP, or Azure), ML Ops practices, and secure data handling. What We Offer: Up to €100,000 Flexible Hybrid 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 ❯

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 ❯

role. Strong programming skills in Python and/or another high-level language commonly used in machine learning. Experience with NLP and Machine Learning frameworks and libraries (e.g., PyTorch, HuggingFace, LangChain, spaCy, NLTK, scikit-learn, etc.). Demonstrated understanding of various techniques for extracting structured data from unstructured sources, indicating expertise in information retrieval. Familiarity with LLMs APIs for pre More ❯

role. Strong programming skills in Python and/or another high-level language commonly used in machine learning. Experience with NLP and Machine Learning frameworks and libraries (e.g., PyTorch, HuggingFace, LangChain, spaCy, NLTK, scikit-learn, etc.). Demonstrated understanding of various techniques for extracting structured data from unstructured sources, indicating expertise in information retrieval. Familiarity with LLMs APIs for pre 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 ❯

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) Cloud platform experience, especially from an ML standpoint … 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 About NICE NICELtd. 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 ❯

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 ❯

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 ❯