Senior Software Developer: Models Team (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.

About the Product

Token Factory is focused on building a next-generation platform that enables companies to seamlessly integrate AI into their products and workflows. Our vision is to create a powerful, open, and scalable alternative for deploying and managing AI systems—making advanced AI infrastructure more accessible to both fast-growing startups and large enterprises.

We work with a wide range of customers, from AI-first companies to established technology organisations, helping them run AI workloads reliably at scale. Our goal is to become a leading platform for high-performance AI inference, delivering predictable latency, strong reliability, and the ability to scale to meet demanding production needs.

Customer feedback plays a central role in how we build—our development process is highly iterative and closely aligned with real-world use cases.

About the Team

The Models Team is responsible for onboarding state-of-the-art (SOTA) open-source models into Nebius TokenFactory, including models such as DeepSeek V4 Pro, GLM 5.1, Kimi K2.6, and Minimax M2.7. A major focus of the team is serving large-scale AI models efficiently and reliably in production.

To achieve this, we work on advanced inference and systems optimization techniques, including:

Cache-aware routing

NUMA-aware deployments

KV-cache offloading

Disaggregated serving architectures

Autoscaling with high-speed model loading over InfiniBand / RoCE

The team maintains and extends forks of leading inference frameworks such as vLLM and TRT-LLM . We have deep expertise in production-scale model serving and regularly support the Solutions Architects team on the most demanding customer PoCs.

To operate efficiently at scale, we invest heavily in tooling and automation.

Examples include:

Performance, quality, and smoke-testing frameworks

Hyperparameter optimization for inference framework configurations

Gibberish detection systems

Automated rollout pipelines for inference framework upgrades

Diagnostics and observability tooling