Requirements

• 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

Nice to Haves

• Experience with long-context modeling, memory systems, sparse or linear attention, model distillation, distributed training, or efficient inference

What You'll Be Doing

• 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

Perks and 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