51 to 75 of 86 Permanent Hugging Face Jobs

Architectures: Cloud expertise (AWS/Azure/GCP); emerging LLM architectures. GenAI Frameworks & Platforms: Proficient with Data & AI platforms (Azure AI, Vertex AI, Databricks, Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented ...

Architectures: Cloud expertise (AWS/Azure/GCP); emerging LLM architectures. GenAI Frameworks & Platforms: Proficient with Data & AI platforms (Azure AI, Vertex AI, Databricks, Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented ...

Architectures: Cloud expertise (AWS/Azure/GCP); emerging LLM architectures. GenAI Frameworks & Platforms: Proficient with Data & AI platforms (Azure AI, Vertex AI, Databricks, Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

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, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput ...

optimisation Hands-on experience training, evaluating, and deploying ML models in real-world systems Proficiency with PyTorch (preferred) or TensorFlow; familiarity with the Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow ...

TypeScript-based agent frameworks. Design agent evaluation strategies using real-world execution data and human-in-the-loop signals. Integrate LLM APIs (OpenAI, Anthropic, Hugging Face, etc.) into product workflows and backend services written in TypeScript and Golang. Prototype and ship AI-powered product capabilities across the platform ...

scientists, software engineers, and product managers to identify and quantify risks associated with models Leverage a broad stack of technologies - from foundational frameworks (PyTorch, Hugging Face), to orchestration tools (LangChain, Vector Databases) to LLMOps, observability platforms, and more - to reveal the insights hidden within huge volumes of multi ...

scientists, software engineers, and product managers to identify and quantify risks associated with models Leverage a broad stack of technologies - from foundational frameworks (PyTorch, Hugging Face), to orchestration tools (LangChain, Vector Databases) to LLMOps, observability platforms, and more - to reveal the insights hidden within huge volumes of multi ...

scientists, software engineers, and product managers to identify and quantify risks associated with models Leverage a broad stack of technologies - from foundational frameworks (PyTorch, Hugging Face), to orchestration tools (LangChain, Vector Databases) to LLMOps, observability platforms, and more - to reveal the insights hidden within huge volumes of multi ...