LLM Researcher
At a glance
Mid-level AI Research role at Oddin. Remote · contract.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Adapt existing language models or train new ones for customer-facing applications
- Turn promising prototypes into production services that are dependable, maintainable and observable
- Build systems using RAG, model reasoning, tool use and creative content generation
- Deploy, monitor and connect language-model systems to the wider solution
- Create dynamic game commentary and interactive avatars using language and vision models
What you bring
- You have solid experience running LLMs in production, covering model training, fine-tuning, inference and tool integration
- You have built RAG systems and worked with vector or graph databases
- You can deploy, monitor and integrate these systems, and understand function calling, structured outputs and agent workflows
- You’re proficient in Python and libraries such as PyTorch, Hugging Face Transformers or FastAPI
Who this fits
This contractor role suits a mid-level researcher with hands-on production LLM experience. It is remote, with the option to work from the Prague office; the role involves collaborating with ML engineers, product developers and domain experts.
From the employer
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
- 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:
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