Senior Software Engineer (Token Factory)

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.

Experience with developing web services.

A commitment to maintaining extreme rigor in all job-related activities.

Nice to have:

Previous experience working with language models or other similar NLP technologies.

A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.