Senior ML Engineer (Token Factory)
About this role
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.
About the role:
Token Factory is a part of Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to deploy at massive scale.
Responsibilities
- Develop and optimize low-level kernels and runtime components for AI inference
- Improve performance of inference engines GPU platforms
- Profile and debug system-level and hardware-level performance issues
- Integrate support for new hardware architectures (Hopper, Blackwell, Rubin)
- Collaborate with ML and backend teams to optimize end-to-end execution
- Required Qualifications:
- Strong proficiency in C++, OR expertise in GPU programming with a focus on low-level high-performance coding and memory management
- Experience in GPU programming or systems-level software development, e.g. operating system internals, kernel modules, or device drivers
- Hands-on experience with profiling and debugging tools to identify performance issues on both CPUs and GPUs, and the ability to optimize code based on those findings.
- Solid understanding of CPU/GPU architecture and memory hierarchy
- Preferred Qualifications:
- Experience with GPU computing programming: CUDA, ROCm, CUTLASS, Cute, ThunderKittens, Triton, Pallas, Mosaic GPU
- Familiarity with ML inference runtimes (e.g. TensorRT, TVM)
- Knowledge of Linux internals, drivers, or compiler toolchains
- Experience with tools like perf, VTune, Nsight, or ROCm profiler
- Familiarity with popular inference engines (e.g. such as vLLM, sglang, TGI)
- We conduct coding interviews as part of the process.