Senior Applied Scientist, Efficient LLM Inference & Model Optimization

Details

Nebius is building a full-stack AI cloud platform supporting developers and enterprises from data and model training through production deployment. The Nebius Token Factory team is looking for an Applied Scientist to turn frontier inference bottlenecks into research problems, publish credible work, and help ship results into production. This role combines rigorous research, strong coding, experimentation, prototyping, and production optimization.

Responsibilities

• Own focused research projects from hypothesis through experimentation, ablation, prototyping, and production handoff.
• Prepare internal reports, technical blogs, or papers when the work is externally credible.
• Partner with machine learning engineers to turn research prototypes into production components.
• Define and execute research programs in efficient LLM and VLM inference with measurable production impact.
• Invent, evaluate, and productionize methods for quantization, QAT, distillation, speculative decoding, KV-cache reuse and compression, long-context inference, MoE routing, and model/runtime co-optimization.
• Build prototypes in PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, then work with machine learning and platform engineers to productionize them.
• Design evaluation methodologies covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token.
• Publish papers, technical reports, blog posts, and open-source artifacts.
• Collaborate with machine learning, GPU kernel, backend infrastructure, product, and customer teams to select high-leverage research opportunities.
• Mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs.

Requirements

• PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related field.
• Strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas.
• Strong hands-on coding ability in Python and PyTorch, with the ability to move quickly from ideas to experiments and prototypes.
• Deep understanding of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs.
• Strong experimental design skills, including ablations, baselines, metrics, statistical reasoning, and failure analysis.
• Excellent written and verbal communication.

Nice-to-Have Qualifications

• First-author publications in NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, HPCA, or comparable venues.
• Experience deploying machine learning models or inference optimizations in production.
• Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals.
• Experience with post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation connected to inference quality or efficiency.
• Open-source research artifacts, widely used benchmarks, high-quality technical blogs, or invited talks in efficient AI systems.

Benefits

• Base compensation range of $195,200–$262,200 USD.
• 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) plan with up to a 4% company match and immediate vesting.
• 20 weeks of paid parental leave for primary caregivers and 12 weeks for secondary caregivers.
• Remote work reimbursement of up to $85 per month for mobile and internet.
• Company-paid short-term disability, long-term disability, and life insurance coverage.
• Career growth and learning opportunities, flexibility and ownership, a collaborative and innovative culture, and the opportunity to work on impactful AI projects.

Applicants must be authorized to work in the country in which they apply and must provide proof of employment eligibility as a condition of hire. Nebius is an equal opportunity employer and provides accommodations during the application process when needed.