Senior Applied Scientist, Efficient LLM Inference & Model Optimization

About the role

Nebius is seeking a scientist to turn frontier LLM and VLM inference bottlenecks into research questions and production capabilities. You will own focused research and optimization projects, conduct rigorous experiments, and produce prototypes and technical artifacts. Your work will span quantization, distillation, speculative decoding, and model/runtime co-optimization to improve inference quality, latency, and throughput.

Responsibilities

• Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff.
• Develop and evaluate methods spanning quantization, quantization-aware training, distillation, speculative decoding, KV-cache reuse, and model/runtime co-optimization.
• Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks and collaborate with engineers to turn them into production components.
• Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation.
• Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism.
• Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, and cost per token.
• Work with cross-functional teams to select research priorities with measurable production impact.
• Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists.

Required skills

• Python
• PyTorch
• LLMs
• VLMs
• Transformer inference
• Model compression
• Quantization
• Experimental design

Nice to have

• vLLM
• SGLang
• TensorRT-LLM
• FlashAttention
• FlashInfer
• Triton
• CUDA
• Distributed inference
• SFT
• RLHF

Qualifications

• PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline
• Strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, or serving systems

Benefits

• Competitive compensation
• Career growth and learning opportunities
• Flexibility and ownership
• Collaborative and innovative culture

About the Company

Nebius is building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment. Listed on Nasdaq and headquartered in Amsterdam, the company has a global footprint with R&D hubs across Europe, the UK, North America and Israel.