About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role This role is for Nebius AI R&D, a team focused on applied research and the development of AI-heavy products. Examples of applied research that we have recently published include: investigating how test-time guided search can be used to build more powerful agents; dramatically scaling task data collection to power reinforcement learning for SWE agents; maximizing efficiency of LLM training on agentic trajectories. One example of an AI product that we are deeply involved in is Nebius Token Factory — an inference and fine-tuning platform for AI models. This role will require expertise in distributed systems to build large-scale LLM training platform. Your responsibilities will include: Designing and developing LLM training platform. Maintaining our ML infrastructure, ensuring optimal performance, scalability and reliability. Improving job scheduling strategies to minimize resource fragmentation. We expect you to have: 5+ years of professional software development experience. Strong software engineering skills (we mostly use Python and Go). Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing.
