LLM Researcher

Oddin · Prague (Remote) · posted Sep 15, 2026

Open to candidates in Czechia

Contractsenior
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What this role actually asks for

Extracted by RemoteHunt

Must have

  • •LLMs in production (training, fine-tuning, inference)
  • •RAG-based systems and vector/graph databases
  • •Deploying, monitoring, and integrating LLM systems
  • •Function calling, structured output, agentic reasoning
  • •Python, PyTorch, Hugging Face Transformers, FastAPI

Nice to have

  • •Sports broadcasting or data-driven content generation
  • •Multimodal LLMs
  • •Efficient model serving tools (vLLM, Triton, DeepSpeed)
  • •Open-source AI contributions or research publications

Tools and technologies

LLMRAGPyTorchHugging Face TransformersFastAPIvLLMTritonDeepSpeed

The full posting

About the Role

We are looking for an experienced LLM Researcher to help us build intelligent, automated systems that enhance customer-facing applications. In this role, you are expected to utilize, optimize and finetune existing language models or train new ones, more adapted to our use cases - and turn successful prototypes into reliable, maintainable, and observable production services . Your work will directly contribute to the development of dynamic, real-time commentary content for games such as FIFA , NBA , or interactive avatars.

This is a remote role with an option to join our Prague office , offering the opportunity to work with cutting-edge LLM frameworks, retrieval-augmented generation (RAG), and multimodal models that process both language and vision. You will collaborate with a small, fast-moving team of ML engineers, product developers, and domain experts to design systems that combine reasoning, tool use, and creative content generation.

Responsibilities: Must-have:

  • Solid experience with LLMs in production environments, including training , fine-tuning , inference , and tool integration .

  • Experience building RAG-based systems and working with vector or graph databases.

  • Experience deploying, monitoring and integrating these systems into the overall solution.

  • Strong understanding of function calling , structured output generation , and agentic reasoning workflows .

  • Proficiency in Python and key libraries (e.g., PyTorch, Hugging Face Transformers, FastAPI). Nice-to-have:

  • Experience with sports broadcasting or data-driven content generation (e.g., live commentary, analytics).

  • Familiarity with multimodal LLMs and integrating textual and visual inputs.

  • Familiarity with tools like vLLM, Triton, or DeepSpeed for efficient model serving.

  • Contributions to open-source AI tools or research publications in NLP, multimodal AI, or agent systems.

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