276 to 300 of 336 Hugging Face Jobs

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

large language model inference, similarity 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 - of large scale production AI systems. More ❯

SQL/NoSQL databases. Experience with API development, web scraping/crawling, and data integration. Practical exposure to on premise AI model deployment and open-source AI frameworks (e.g., Hugging Face, LangChain). Ability to assess AI tools and recommend optimization for performance improvements. Strong consulting and communication skills — able to translate technical concepts into business value. Bachelor More ❯

SQL/NoSQL databases. Experience with API development, web scraping/crawling, and data integration. Practical exposure to on premise AI model deployment and open-source AI frameworks (e.g., Hugging Face, LangChain). Ability to assess AI tools and recommend optimization for performance improvements. Strong consulting and communication skills — able to translate technical concepts into business value. Bachelor More ❯

practices. What We’re Looking For Strong academic background in Computer Science, ML, AI, or a related field. Deep hands-on experience with Python and ML frameworks (PyTorch, TensorFlow, Hugging Face). Proven background in MLOps, including model versioning, CI/CD for ML, and production monitoring. Experience building robust backend systems and APIs to serve ML models More ❯

learning. Advanced Python Development Proficiency: Experience with OOP, and data-validation libraries such as Pydantic. Deep familiarity with Python and its ecosystem for AI/ML, including libraries likePyTorch, Hugging Face Transformers, andscikit-learn. Experience withdata manipulationusing libraries such asPandasandNumPy, and familiarity withparallelizationorasynchronous programming. Proficiency in Test-Driven Development (TDD) and an understanding of Python testing libraries such More ❯

with LLMs and AI-powered search systems. Design and implement Retrieval-Augmented Generation (RAG) pipelines using open-source tools like LangChain, Langflow, and DataStax Vector Search. Fine-tune LLMs (Hugging Face, OpenAI, Cohere, or similar) to improve response quality and domain-specific performance. Optimize embedding models for better semantic search and document retrieval. Integrate AI-driven solutions with More ❯

Java, and SQL/NoSQL databases, along with API development and data integration techniques. Practical experience with deploying AI models on-premise and utilizing open-source frameworks such as Hugging Face and LangChain. Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Engineering, or a related field. Benefits: 25 days annual leave plus a flexible More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯