Collaborate with over 250 AI Engineers on state-of-the-art AI capabilities.
Participate in the development of agentic systems that reason, plan, and act.
Work alongside AI agents, RAG pipelines, and LLM orchestration.
Engage in all aspects of project development from ideation to production deployment.
Learn and grow through seminars, courses, and professional conferences.

MSc/PhD student focusing on AI, computer science, engineering, or a related field (thesis in a relevant area is a plus).
Hands-on experience building with LLMs — e.g. prompting, fine-tuning, evaluation, or working with LLM APIs.
Practical experience with agentic frameworks and concepts: agent orchestration, tool use, multi-step planning, or frameworks such as LangGraph or LangChain.
Experience with or strong understanding of RAG (Retrieval-Augmented Generation) — embeddings, vector stores, retrieval pipelines.
Solid foundational ML/DL knowledge (this is a supporting skill, not the core focus of the role).
Substantial experience programming in Python, including building and integrating multi-component systems (not just notebooks/scripts).
Highly motivated to solve real-world problems and create high impact in practice.
Team player with great communication skills, who can also work independently and methodically.
Capacity to work at least 2.5 days a week, with studies expected to continue for at least 1.5 years.

Data Science Student

Key skills