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About the Role

Nebius Token Factory seeks scientists to transform frontier inference bottlenecks into research problems, publish credible work, and ship results into production. This role involves designing experiments, writing code, collaborating with engineers, and converting research into deployed inference capabilities. A Senior Applied Scientist will own research and production optimization projects, producing high-quality technical work, code, experiments, and prototypes for engineers.

Responsibilities

Own focused research projects from hypothesis through experiment, ablation, prototype, and production handoff.
Prepare internal reports, technical blogs, or papers for externally credible work.
Partner directly with MLEs to ensure research prototypes become usable 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, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization.
Build high-quality prototypes in PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, then work with MLEs and platform engineers to productionize them.
Design rigorous evaluation methodology covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token.
Publish papers, technical reports, blog posts, and open-source artifacts that build external credibility for Nebius Token Factory.
Collaborate with MLE, GPU kernel, backend infrastructure, product, and customer teams to choose high-leverage research bets.
Mentor engineers and scientists on experimental design, scientific rigor, and model/system tradeoffs.

Requirements

PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied math, 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; ability to move from idea to experiment to prototype quickly.
Deep understanding of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving tradeoffs.
Strong experimental design skills, including ablations, baselines, metrics, statistical reasoning, and failure analysis.
Excellent written and verbal communication.
First-author publications in NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, HPCA, or comparable venues.
Experience deploying ML 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 when connected to inference quality or efficiency.
Open-source research artifacts, widely used benchmarks, high-quality technical blogs, or invited talks in efficient AI systems.

Skills

Python
PyTorch
LLMs
VLMs
Transformer inference
Decoding algorithms
Model compression
Quantization
Production-serving tradeoffs
Experimental design
Ablations
Baselines
Metrics
Statistical reasoning
Failure analysis
Triton
CUDA
vLLM
SGLang
TensorRT-LLM
NVIDIA Dynamo
FlashAttention
FlashInfer
PyTorch internals
Post-training
SFT
DPO
RLHF
RLAIF
Preference optimization
Synthetic data generation

Location

Amsterdam

Work Type

Full-time

Experience Level

Senior

Education Level

Benefits

Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams

About the Company

Nebius is leading a new era in cloud infrastructure for the global AI economy, building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment.
Built by engineers, for engineers, Nebius addresses challenges across compute, storage, networking, and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, Nebius has a global footprint with R&D hubs across Europe, the UK, North America, and Israel.
The team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software, and AI R&D.

Equal Opportunity

Nebius is an equal opportunity employer committed to fostering an inclusive and diverse workplace.
We provide equal employment opportunities in all aspects of employment without discrimination based on 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.
Applicants must be authorized to work in the country of application and will be required to provide proof of employment eligibility.
Accommodations are available during the application process upon request.