Senior Applied Scientist, Efficient LLM Inference & Model Optimization
Nebius — Zurich, Zurich, Switzerland · In-Person · Senior
Role description
Role Overview
Nebius is seeking a Senior Applied Scientist to lead research projects in efficient LLM and VLM inference, develop and evaluate methods, and build prototypes using PyTorch and other tools. The role will involve investigating LLM request routing and scheduling strategies, multi-node inference, and developing rigorous evaluations.
What You Will Do
The Senior Applied Scientist will lead research projects, develop and evaluate methods, build prototypes, and work with engineering teams to bring promising results into production. They will also research LLM request routing and scheduling strategies, investigate multi-node inference, and develop rigorous evaluations.
Why It Might Be a Fit
The ideal candidate will have a PhD in a relevant field, a strong publication record, and strong Python and PyTorch implementation skills. They will also have deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs.
Requirements
- 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, serving systems, or related areas
- Strong Python and PyTorch implementation skills
- Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs
- Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis
- Excellent written and verbal communication
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