Senior Research Scientist, Architectures Research

Nebius Group

Senior Research Scientist developing efficient model architectures for Nebius, a cloud infrastructure platform for the global AI economy. Leading experiments, publications, open-source contributions, and research mentorship.

Posted 8/10/2026full-timeRemote • 🇬🇧 United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in machine learning with a focus on transformers, attention mechanisms, and modern model architectures. Proven ability to design rigorous experiments, publish original research, and mentor researchers while leading independent research initiatives.

Highest-signal resume keywords

PhD In Machine LearningTransformers And Attention MechanismsPython ProgrammingDeep-Learning FrameworksModel Training And Evaluation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Experimental DesignModel DistillationDistributed TrainingEfficient InferenceLong-Context ModelingMemory SystemsSparse Or Linear Attention

Soft Skills

Technical CommunicationMentoring

Certifications & Qualifications

Proof Of Employment Eligibility

Industry Keywords

Machine LearningModel ArchitecturesResearch PublicationOpen-Source Contributions

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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
Must be authorized to work in the country in which they apply and provide proof of employment eligibility as a condition of hire

Benefits

Comp & perks

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
Fast moving
Bold thinking
Constant growth
Meaningful impact
Trust and real ownership
Opportunity to shape the future of AI
Equal employment opportunities and inclusive workplace
Application process accommodations