About the role

Applied Research Intern building proactive AI and customer world models at Block. Developing research from machine learning experiments through production systems serving millions of customers and sellers.

Responsibilities

Build foundations of proactive intelligence for Block's Customer World Model
Own a research problem end-to-end: frame questions, develop methods, run experiments, publish findings, and potentially ship work into production systems
Work across representation learning, foundation models, reinforcement learning, causal reasoning, agentic systems, and product intelligence
Build rich customer representations from event streams, financial activity, operational signals, and behavioral data
Develop systems that anticipate customer needs and initiate helpful actions
Build agents that reason over customer world models and take actions in real environments
Develop methods that improve continuously from real-world outcomes
Build evaluation frameworks predicting real-world performance, trust, and customer value
Collaborate across scientific research and product deployment

Currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field, and returning to that program after the co-op
Strong foundations in modern machine learning, including deep learning, optimization, representation learning, and foundation models
Experience conducting independent research and translating ideas into working systems
Fluency in Python and experience with PyTorch, JAX, or similar frameworks
Evidence of research excellence through publications, open-source contributions, technical leadership, or equivalent work
Fall/Winter 2026 co-op commitment for 8 months, with flexible start in September 2026
Experience with large language models and agentic systems
Experience with reinforcement learning, reward modeling, or sequential decision-making
Experience with representation learning for structured, temporal, or graph data
Familiarity with large-scale training and production ML systems
Interest in building AI systems that directly affect customer outcomes

Direct mentorship from researchers working on the future of proactive intelligence at Block
Access to large-scale datasets, modern infrastructure, frontier models, and substantial compute resources
Opportunities to publish and contribute to open-source projects
A chance to shape foundational technology that could power the next generation of Block products
Exposure to both scientific research and product deployment, with a clear path from idea to impact
Remote work
Medical insurance
Flexible time off
Retirement savings plans
Modern family planning