Senior Backend Developer Token Factory

Why work at Nebius

Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Where we work

Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

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 plat
• form.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.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess.