Staff Machine Learning Engineer, LLM Inference Optimization

div class= content-intro p strong About Nebius: /strong /p p 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 amp;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 amp;D. /p /div div class= _3iDTPbvLZJ renderer-heading-wrapper data-testid= renderer-heading-wrapper data-level= 2 h2 id= Role-Summary data-local-id= ad213d8fe4e2 data-renderer-start-pos= 1929 Role Summary /h2 /div p data-renderer-start-pos= 1943 data-local-id= 4daa64b4c380 Nebius Token Factory is building production-grade inference for open-source, customer, and internally optimized models. This role owns the path from model artifact to fast, reliable, cost-efficient endpoint. The work sits at the intersection of model internals, inference engines, serving architecture, benchmarking, and production deployment. /p div class= _3iDTPbvLZJ renderer-heading-wrapper data-testid= renderer-heading-wrapper data-level= 2 h2 data-local-id= 6b105a288faf data-renderer-start-pos= 2508 nbsp; /h2 h2 id= What-You-Will-Do data-local-id= 6b105a288faf data-renderer-start-pos= 2508 What You Will Do /h2 /div ul class= ak-ul data-local-id= ebbff5d80805 data-indent-level= 1 li p data-renderer-start-pos= 2528 data-local-id= c5115fb223c0 Own a platform-level optimization pillar such as quantization, speculative decoding, span data-highlighted= true data-vc= highlighted-text KV /span -cache optimization, engine selection, or long-context serving. /p /li li p data-renderer-start-pos= 2682 data-local-id= 0ffc3414d75f Create reusable evaluation, benchmarking, and rollout frameworks across multiple model families. /p /li li p data-renderer-start-pos= 2782 data-local-id= b1093d4c9089 Provide technical direction to MLEs, Applied Scientists, GPU kernel engineers, and infrastructure engineers on shared performance goals. /p /li li p data-renderer-start-pos= 2922 data-local-id= ba8442a0b3db Optimize LLM and span data-highlighted= true data-vc= highlighted-text span class= _1mT5xdRAKS span class= _0nmozVaHVx _2V7sgO2M4S _3BoeIDwZ7G _30zrXRyxdf _0ReiIH7zJH data-testid= definition-highlighter VLM /span /span /span endpoints for latency, throughput, memory efficiency, GPU utilization, quality, and cost per token. /p /li li p data-renderer-start-pos= 3046 data-local-id= 295f060f2f89 Deploy, configure, benchmark, and extend inference engines such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, span data-highlighted= true data-vc= highlighted-text NVIDIA /span Dynamo, or similar systems. /p /li li p data-renderer-start-pos= 3204 data-local-id= a92060bc9227 Build and productionize model-compression workflows, including quantization, quantization-aware training, distillation, low-bit serving, and accuracy recovery. /p /li li p data-renderer-start-pos= 3367 data-local-id= fc94ad87ea7d Implement or integrate speculative decoding, draft-model approaches, span data-highlighted= true data-vc= highlighted-text KV /span -cache optimization, prefix caching, chunked prefill, continuous batching, and disaggregated prefill/decode serving. /p /li li p data-renderer-start-pos= 3558 data-local-id= 767163fd69ef Build reproducible benchmark harnesses for span data-highlighted= true data-vc= highlighted-text TTFT /span , span data-highlighted= true data-vc= highlighted-text TPOT /span , tokens per second per GPU, p95/p99 latency, GPU memory, reliability, and cost per token. /p /li li p data-renderer-start-pos= 3705 data-local-id= 08931f048a7e Partner with GPU kernel engineers and platform engineers to diagnose bottlenecks across model code, kernels, runtime, scheduler, gateway, and cluster layers. /p /li li p data-renderer-start-pos= 3866 data-local-id= 40fc2b50527b Write clear design docs, performance reports, rollout plans, and customer-facing technical explanations. /p /li /ul div class= _3iDTPbvLZJ renderer-heading-wrapper data-testid= renderer-heading-wrapper data-level= 2 h2 id= Required-Qualifications data-local-id= d808b8c02bc9 data-renderer-start-pos= 3974 Required Qualifications /h2 /div ul class= ak-ul data-local-id= 000c2bf27478 data-indent-level= 1 li p data-renderer-start-pos= 4001 data-local-id= 8bcf8dd9c7f9 Strong Python and PyTorch engineering skills. /p /li li p data-renderer-start-pos= 4050 data-local-id= 781d2e3f4c3f Hands-on experience deploying or optimizing LLM, span data-highlighted= true data-vc= highlighted-text VLM /span , or high-throughput transformer inference systems. /p /li li p data-renderer-start-pos= 4157 data-local-id= 604abc69fbd4 Practical knowledge of at least one modern inference stack such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, span data-highlighted= true data-vc= highlighted-text NVIDIA /span Dynamo, Ray Serve, KServe, or equivalent internal systems. /p /li li p data-renderer-start-pos= 4346 data-local-id= 3815fcf1bdd9 Strong understanding of transformer inference bottlenecks, including span data-highlighted= true data-vc= highlighted-text KV /span cache, attention, memory bandwidth, batching, parallelism, and long-context serving. /p /li li p data-renderer-start-pos= 4506 data-local-id= e7ade27b40b8 Ability to reason quantitatively about latency, throughput, quality, utilization, and cost tradeoffs. /p /li li p data-renderer-start-pos= 4611 data-local-id= ba5ac6530c91 Strong communication skills and ability to collaborate with research, kernel, infrastructure, product, and customer teams. /p /li /ul div class= _3iDTPbvLZJ renderer-heading-wrapper data-testid= renderer-heading-wrapper data-level= 2 h2 id= Preferred-Qualifications data-local-id= 8d0c1267a411 data-renderer-start-pos= 4737 Preferred Qualifications /h2 /div ul class= ak-ul data-local-id= 60367df2c185 data-indent-level= 1 li p data-renderer-start-pos= 4765 data-local-id= adcfa560c32c Experience with quantization-aware training, post-training quantization, span data-highlighted= true data-vc= highlighted-text FP8 /span , span data-highlighted= true data-vc= highlighted-text span class= _1mT5xdRAKS span class= _0nmozVaHVx _2V7sgO2M4S _3BoeIDwZ7G _30zrXRyxdf _0ReiIH7zJH data-testid= definition-highlighter INT8 /span /span /span , span data-highlighted= true data-vc= highlighted-text INT4 /span , span data-highlighted= true data-vc= highlighted-text NVFP4 /span , span data-highlighted= true data-vc= highlighted-text MXFP4 /span , span data-highlighted= true data-vc= highlighted-text AWQ /span , span data-highlighted= true data-vc= highlighted-text GPTQ /span , SmoothQuant, or related techniques. /p /li li p data-renderer-start-pos= 4919 data-local-id= 819dcc6d2bb4 Experience with distillation, speculative decoding, EAGLE, Medusa, multi-token prediction, or other inference acceleration methods. /p /li li p data-renderer-start-pos= 5054 data-local-id= 15844e70e97e Experience with agentic workloads, including tool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration. /p /li li p data-renderer-start-pos= 5200 data-local-id= 7cd4bee1cb99 span data-highlighted= true data-vc= highlighted-text CUDA /span or Triton familiarity, even if the role is not primarily a kernel-engineering role. /p /li li p data-renderer-start-pos= 5292 data-local-id= f030cb084e2a Open-source contributions to vLLM, SGLang, TensorRT-LLM, FlashInfer, LMCache, PyTorch, Triton, Ray, KServe, or related projects. /p /li /ul p nbsp; /p div class= content-conclusion p strong Benefits amp; Perks: /strong /p ul li Competitive compensation /li li Career growth and learning opportunities /li li Flexibility and ownership /li li Collaborative and innovative culture /li li Opportunity to work on impactful AI projects /li li International environment and talented teams /li /ul p strong What's it like to work at Nebius: /strong /p p Fast moving nbsp;- Bold thinking nbsp;- Constant growth nbsp;- Meaningful impact nbsp;- Trust and real ownership nbsp;- Opportunity to shape the future of AI nbsp; /p p strong Equal Opportunity Statement: /strong /p p Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. /p p Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. nbsp; /p p If you need accommodations during the application process, please let us know. /p /div Find more English Speaking Jobs in Switzerland on Arbeitnow