Senior Applied Scientist, Efficient LLM Inference & Model Optimization
Nebius — Berlin, Germany · In-Person · Senior
Role description
Role Overview
Nebius is looking for a Senior Applied Scientist to lead research projects in efficient LLM and VLM inference, develop and evaluate methods, and build prototypes to turn them into production components.
What You Will Do
The role involves leading research projects, developing and evaluating methods, building prototypes, and collaborating with engineering teams to bring promising results into production.
Why It Might Be a Fit
The ideal candidate will have a strong publication record, deep knowledge of LLMs, VLMs, and production-serving trade-offs, and excellent written and verbal communication skills.
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