Senior Machine Learning Engineer, LLM Inference Optimization

Навыки

• AI-агенты
• Коммуникация
• Многопоточность
• CUDA / ONNX / TensorRT
• Распределённые системы
• LLM
• Инференс LLM

О компании и продукте

• 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.
• Nebius Token Factory is building an AI training and model post-training capability for frontier model improvement. This role owns the infrastructure that makes large-scale training and RL experiments possible, reliable, reproducible, and efficient. The work sits at the intersection of distributed systems, GPU performance, model training frameworks, RL pipelines, and production engineering.

Требования

• Strong Python and PyTorch engineering skills
• Hands-on experience deploying or optimizing LLM, VLM , or high-throughput transformer inference systems
• Practical knowledge of at least one modern inference stack such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, Ray Serve, KServe, or equivalent internal systems
• Strong understanding of transformer inference bottlenecks, including KV cache, attention, memory bandwidth, batching, parallelism, and long-context serving
• Ability to reason quantitatively about latency, throughput, quality, utilization, and cost tradeoffs
• Strong communication skills and ability to collaborate with research, kernel, infrastructure, product, and customer teams
• Nice - to - have s
• Experience with quantization-aware training, post-training quantization, FP8 , INT8 , INT4 , NVFP4 , MXFP4 , AWQ , GPTQ , SmoothQuant, or related techniques
• Experience with distillation, speculative decoding, EAGLE, Medusa, multi-token prediction, or other inference acceleration methods
• Experience with agentic workloads, including tool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration
• CUDA or Triton familiarity, even if the role is not primarily a kernel-engineering role
• Open-source contributions to vLLM, SGLang, TensorRT-LLM, FlashInfer, LMCache, PyTorch, Triton, Ray, KServe, or related projects
• Key employee benefits in the US
• 401(k) plan: Up to 4% company match with immediate vesting
• Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers

Условия

• Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families
• Remote work reimbursement: Up to $85/month for mobile and internet
• Disability & life insurance : Company-paid short-term, long-term and life insurance coverage

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