Applied Research Intern, Proactive Intelligence & Customer World Models (PhD / Graduate Co-op)

📋 Description

• Own a research problem end-to-end: frame question, develop methods, run experiments, publish findings, and ship to production.
• Work at the intersection of representation learning, foundation models, RL, and product intelligence.
• Build customer world models to understand goals, context, and needs.
• Develop proactive intelligence that anticipates needs and initiates actions.
• Create agentic decision systems that reason over models and act in real environments.
• Design evaluation frameworks for real-world performance and trust.

🎯 Requirements

• Currently enrolled in MS/PhD in CS/ML/Stats/Math/OR and returning after the co-op.
• Strong foundations in modern ML: deep learning, optimization, representation learning, foundation models.
• Experience conducting independent research and translating ideas into working systems.
• Fluency in Python; experience with PyTorch, JAX, or similar.
• Evidence of research excellence: publications, OSS contributions, or leadership.
• Nice to have: experience with LLMs, agentic systems, or RL/reward modeling.

🎁 Benefits

• Direct mentorship from researchers working on the future of proactive intelligence at Block.
• Access to large-scale datasets, modern infrastructure, frontier models, and compute resources.
• Opportunities to publish and contribute to open-source projects.
• A chance to shape foundational technology powering Block products.
• Exposure to both scientific research and product deployment, with a clear path from idea to impact.