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.
United Kingdom