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Senior ML Engineer (Token Factory)

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EMP:Technology
Amsterdam, Netherlands; Berlin, United Kingdom; Prague, Czech Republic; Remote - Europe
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<div class="content-intro"><p><strong>.

Acerca de

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.

</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><p><strong>The role</strong></p> <p>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 a high-performance inference and fine-tuning platform designed to push foundation models to their hardware limits.

Our mission is to maximize throughput, minimise latency, and optimise cost-per-token across tens of thousands of GPUs.

</p> <p> </p> <p><strong>Some directions we are currently working on, and which you can be a part of:</strong></p> <ul> <li>Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups.

Squeezing the maximum performance for a wide range of LLM architectures at scale (e.

, GPT-OSS, Kimi K2.

5, DeepSeek V3.

</li> <li>Inference engines support: Implement novel speculative decoding architectures, optimise components of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.

</li> <li>Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and.

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