<div class="content-intro"><p><strong>.
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.
</p> <p>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.
</p> <p>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.
</p></div><h2><strong>The role</strong></h2> <p>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:</p> <ul> <li><a href=" test-time guided search can be used to build more powerful agents;</li> <li>dramatically <a href="https://nebius.
com/blog/posts/scaling-data-collection-for-training-swe-agents">scaling</a> task data collection to power reinforcement learning for SWE agents;</li> <li><a href="https://nebius.
com/blog/posts/kvax-open-source-flash-attention-for-jax">maximizing efficiency</a> of LLM training on agentic trajectories.
</li> </ul> <p>One example of an AI product that we are deeply involved in is Nebius Token Factory — an <a href="https://nebius.
com/studio/inference">inference</a> and <a href="https://nebius.
com/services/studio-fine-tuning">fine-tuning</a> platform for AI models.
</p> <p>This role will require expertise in distributed systems to build large-scale LLM training platf.