Senior Applied Scientist, Efficient LLM Inference & Model Optimization

About the role

Nebius is seeking a scientist to research and optimize LLM and VLM inference bottlenecks. You will conduct rigorous experiments, develop prototypes, and translate findings into production capabilities while focusing on areas like quantization, distillation, and distributed inference architectures.

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 (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization.
• Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components.
• Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD).
• Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP).
• Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token.
• Work with MLE, GPU kernel, backend infrastructure, product, and customer 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 on experimental design, scientific rigor, and model/system trade-offs.

Required skills

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

Nice to have

• vLLM
• SGLang
• TensorRT-LLM
• NVIDIA Dynamo
• FlashAttention
• FlashInfer
• Triton
• CUDA
• SFT
• DPO

Qualifications

• PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline.

Benefits

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

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.