1 to 25 of 52 Permanent Hugging Face Jobs

Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 - AI Prompt Engineering Master prompt engineering, learning how to craft ...

Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 - AI Prompt Engineering Master prompt engineering, learning how to craft ...

GitHub, and GitLab. Hands-on experience building, deploying, and scaling AI/ML solutions using frameworks and platforms such as Scikit-learn, PyTorch, TensorFlow, Hugging Face, LangChain, Databricks, Spark, vector databases, cloud services (AWS/Azure), and MLOps tools including MLflow and Kubeflow. Proven ability to develop production ...

Execute, Multi-Agent Collaboration). +2 years with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel) and model APIs (OpenAI, Anthropic, Bedrock, Ollama, Hugging Face). +2 year experience in building agentic AI systems and agentic workflows +2 year experience developing AI and ML algorithms or technologies (e.g. ...

LLMs, multimodal AI, self-supervised learning, reinforcement learning, time-series analytics or foundation models. Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision applications. Strong understanding of experimental design, statistical evaluation, benchmarking and model validation. Experiment tracking and reproducibility tools ...

CrewAI Experience in machine learning development, including training, evaluating, deploying, and monitoring models Experience with deep learning or NLP frameworks, such as PyTorch or Hugging Face Good understanding of software engineering principles, design patterns, and ML lifecycle practices, including MLOps or LLMOps Experience contributing to the delivery ...

expertise. Required Skills & Experience BSc in Machine Learning, Data Science, Computer Science, Mathematics or related field. Experience coding in Python and associated ML packages (HuggingFace, TensorFlow, PyTorch). Have experience of delivering ML solutions to stakeholders. Demonstrate good understanding of AI/ML algorithms for different data types and tasks ...

software. Hands-on experience with technologies such as Azure OpenAI, Azure AI Services, and Azure Machine Learning. Knowledge of modern AI frameworks including LangChain, Hugging Face, PyTorch, or similar technologies. Deep understanding of LLMs, RAG architectures, vector databases, prompt engineering, agentic AI, and multi-agent systems. Experience deploying ...

Solid software engineering fundamentals: Clean Code (SOLID, DRY), DDD, modular architecture, TDD and code quality tooling. Desirable: RAG pipelines, MCP, LLM integration (OpenAI, Gemini, Hugging Face models), LangSmith, TruLens, and agentic frameworks such as LangChain, CrewAI, Autogen, OpenAI Agents and Google ADK. You won't need every technology ...

what 'good' means for a model, build the test set and measure it. Strong grounding in the ML stack, such as PyTorch, scikit-learn, Hugging Face and vector databases, alongside sound software engineering practice. Experience deploying and monitoring models on cloud infrastructure, ideally AWS, with Git, CI/ ...

team practice, such as evaluation standards, release processes, shared tooling or ways of working. Strong Python, with deep working knowledge of PyTorch and the Hugging Face ecosystem. Experience with automatic or model-assisted labelling of visual data, and with dataset quality control. A solid grasp of MLOps: experiment ...

/ML with experience developing and deploying solutions using LLMs, RAG architectures, and modern AI frameworks and protocols (Strands, FastMCP, LangChain, LlamaIndex, Hugging Face, A2A, MCP). Ability to translate multi-layered business problems into technical solutions with experience working directly with business stakeholders to understand requirements ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...

search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large ...