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Oddin

LLM Researcher

Posted 9 days ago
5-10 years experience
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AI Summary

You will develop, optimize, and fine-tune language models to create intelligent, automated systems for customer-facing applications. Your work involves transitioning prototypes into reliable production services, including RAG-based systems and agentic workflows.

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.

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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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