Nebius

Senior Applied Scientist, Efficient LLM Inference & Model Optimization

San Francisco, CA, US$195,200-$262,200Posted 1 month ago

Job Description

About Nebius

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.

### The role

Nebius Token Factory needs scientists who can turn frontier inference bottlenecks into research problems, publish credible work, and then help ship the results into production. This is not a papers-only research role. The Applied Scientist is expected to design rigorous experiments, write strong code, collaborate with engineers, and convert research into deployed inference capabilities.

A Senior Applied Scientist owns well-scoped research and production optimization projects. They can publish or prepare high-quality technical work while also producing code, experiments, and prototypes that engineers can use.

Your responsibilities

:

  • Own focused research projects from hypothesis through experiment, ablation, prototype, and production handoff.
  • Prepare internal reports, technical blogs, or papers when the work is externally credible.
  • 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-ca

Apply for this role

Keep looking

Similar Remote AI Jobs