1 to 25 of 404 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 ❯

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 ❯

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 ❯

in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field. Proficiency in Python, including hands-on experience with machine learning libraries and frameworks (e.g., Pandas, Pytorch, Tensorflow, HuggingFace). Demonstrated experience in data science and machine learning through projects, internships, or prior roles, with exposure to or hands on experience with Gen AI concepts and technologies. Familiarity with 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 … degree in AI, statistics, mathematics, computer science, or a related field. Programming and Frameworks: Hands-on 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: Expertise in prompt engineering, including prompt tuning, chaining More ❯

processing tools and platforms (e.g., SQL, Apache Spark, Hadoop). Knowledge of cloud computing services (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes) is a plus. Hugging Face Ecosystem: Demonstrated experience using Hugging Face tools such as the Transformers library, Datasets, and Tokenizers. Familiarity with integrating pre-trained models and fine-tuning them 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 ❯

with capabilities such as large-scale vector stores for embeddings. Author best practices on the Generative AI ecosystem, when to use which tools, available models such as GPT, Llama, Hugging Face etc. and libraries such as Langchain. Analyze, investigate, and implement GenAI solutions focusing on Agentic Orchestration and Agent Builder frameworks. Contribute to major design decisions and product 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 ❯

/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 ❯

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 ❯

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 ❯