The role

 Nebius AI R&D conducts frontier applied research to make open-source AI highly competitive for real-world use cases. Our Architectures Research stream explores how models can attend, remember, reason, and adapt more effectively, enabling longer and richer workflows at lower computational cost.

 We are looking for a Senior Research Scientist to develop new model architectures and methods in areas such as:

- Efficient, sparse, and adaptive attention

- Long-context models and persistent memory

- Post-training transformation of pretrained models -

 - Selective computation and dynamic inference

 - New architectures for reasoning and continual adaptation 

 Responsibilities

- 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 stream's research direction

 What we expect

 - A PhD or equivalent research experience in machine learning

- Deep knowledge of transformers, attention, language-model training, and modern model architectures

- A strong publication record or comparable evidence of original research

- Experience designing rigorous experiments and drawing clear conclusions from ambiguous results

 - Strong implementation skills in Python and a modern deep-learning framework

- Experience training or evaluating models at scale

 - Clear technical communication and the ability to lead research independently

Experience with long-context modeling, memory systems, sparse or linear attention, model distillation, distributed training, or efficient inference is particularly relevant.