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

Block is hiring graduate research interns for Apollo, its Applied R&D team, to build foundations for proactive intelligence and Customer World Models. The role involves owning research problems from framing and experimentation through publication and potential production deployment, across machine learning, decision systems, and evaluation.

Responsibilities:

• You'll own a research problem end-to-end: framing the question, developing methods, running experiments, publishing findings, and, when successful, shipping your work into production systems used by millions of customers and sellers
• Building rich representations of customers from event streams, financial activity, operational signals, and behavioral data
• Representation learning over long-horizon customer histories
• Event-based foundation models
• Multi-modal customer representations spanning structured, sequential, and graph data
• Memory architectures for long-term customer understanding
• Developing systems that can anticipate customer needs and initiate helpful actions before being asked
• Opportunity detection and next-best-action systems
• Long-horizon planning and decision-making
• Preference and goal inference
• Learning when intervention creates value versus friction
• Building agents that reason over customer world models and take actions in real environments
• Tool use and planning
• Multi-step reasoning over customer state
• Autonomous workflow execution
• Recovery and adaptation under uncertainty
• Developing methods that allow intelligence to improve continuously from real-world outcomes
• Reinforcement learning from customer and product feedback
• Reward modeling and preference learning
• Counterfactual evaluation
• Credit assignment over long decision horizons
• Building evaluation frameworks that predict real-world performance, trust, and customer value
• Simulated customer environments
• Longitudinal evaluation
• Decision quality metrics
• Safety and reliability benchmarks