Senior Research Scientist (Architectures Research)
About this role
Nebius needs a Senior Research Scientist to solve high computational costs and limitations in model capacity by developing new architectures and methods for AI. The Architectures Research stream focuses on helping models attend, remember, reason, and adapt more effectively during long workflows without unnecessary overhead. Researchers in this group tackle complex problems involving sparse attention, persistent memory, and dynamic inference to make open-source AI practical for real-world applications.
Working within a global R&D organization, the incoming scientist will formulate original research questions, execute rigorous experimental programs, and test architectural changes at meaningful model scales. Team members collaborate closely with engineering colleagues to translate theoretical breakthroughs into efficient implementations that actually run in production. Ideal candidates possess a strong background in machine learning research, practical experience training models at scale, and a desire to publish findings while contributing directly to open-source tools.
What you will do
- Formulate original research questions and translate them into rigorous experimental programs.
- Design and evaluate architectural changes at meaningful model scales.
- Develop methods that preserve model quality while reducing training or inference cost.
- Collaborate with engineering teams to validate ideas in efficient implementations.
- Publish research and contribute to open-source models, methods, and tools.
- Mentor researchers and help shape the research direction of the stream.
What you need
- Hold a PhD or equivalent research experience in machine learning.
- Demonstrate deep knowledge of transformers, attention, language-model training, and modern model architectures.
- Showcase a strong publication record or comparable evidence of original research.
- Bring experience designing rigorous experiments and drawing clear conclusions from ambiguous results.
- Possess strong implementation skills in Python and a modern deep-learning framework.
- Demonstrate experience training or evaluating models at scale alongside clear technical communication abilities.
Nice to have
- Experience with long-context modeling
- Experience with memory systems
- Experience with sparse or linear attention
- Experience with model distillation
- Experience with distributed training or efficient inference
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
Skills and tech stack
Questions candidates ask
What locations are available for this role?
The position is based in Israel, the United Kingdom, or available as remote work across Europe.
What does the Architectures Research stream focus on?
The stream explores how models can attend, remember, reason, and adapt more effectively, enabling longer and richer workflows at lower computational cost.
What are the main areas of development for this position?
The scientist will develop new model architectures and methods in areas such as efficient, sparse, and adaptive attention, long-context models, persistent memory, post-training transformation, selective computation, and new architectures for reasoning.