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
- 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).
- 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.
Must-have:
Nice-to-have:
Skills Required
- Production experience with large language models, including training, fine-tuning, inference, and tool integration
- Experience building retrieval-augmented generation systems
- Experience working with vector or graph databases
- Experience deploying, monitoring, and integrating LLM systems into broader solutions
- Strong understanding of function calling, structured output generation, and agentic reasoning workflows
- Proficiency in Python
- Experience with PyTorch, Hugging Face Transformers, and FastAPI
- Experience with sports broadcasting or data-driven content generation
- Familiarity with multimodal large language models and textual and visual inputs
- Familiarity with vLLM, Triton, or DeepSpeed
- Contributions to open-source AI tools or research publications in NLP, multimodal AI, or agent systems
What We Do
Oddin.gg is a global B2B provider of end-to-end esports betting solutions, specializing in esports data science. The company provides betting operators with real-time odds feeds, automated risk management, and embeddable iFrame integrations. By leveraging machine learning and mathematical models, Oddin.gg optimizes partner profitability and user engagement across a wide range of esports titles, including Dota2 and League of Legends.
