101 to 105 of 105 Hugging Face Jobs

across the stack. Key Qualifications Strong proficiency in Java and React/TypeScript Hands-on experience building and deploying LLM-based systems (e.g., OpenAI, Hugging Face Transformers, LangChain, etc.). Deep understanding of AI application architecture, including RAG systems, vector databases, prompt engineering, and fine-tuning. Experience with ...

Python 3.9+, with a solid understanding of object-oriented programming and data structures. Experience with libraries such as PyTorch, OpenCV, PIL/Pillow, and Hugging Face for working with AI/ML models. Familiarity with AWS services, including Lambda, S3, CloudWatch, and Boto3 for automation and deployment. Expertise ...

experience using and extending Visual Studio Code (extensions, integrations, workflows). Familiarity with AI developer tools, LLM APIs, and agent frameworks (e.g., OpenAI, LangChain, Hugging Face). Ability to build and explain end-to-end demos using modern dev tooling and workflows (git, CI/CD, cloud platforms ...

applications. Technical Skills: Strong knowledge of tools like Dialogflow, Microsoft Bot Framework, Rasa, and Amazon Lex. Expertise with libraries such as spaCy, NLTK, and Hugging Face Transformers. Practical experience with Python, REST APIs, and dialog model training data preparation. Excellent ability to present complex AI concepts clearly ...

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 ...