Block
AppliedResearchIntern,ProactiveIntelligence&CustomerWorldModels(PhD/GraduateCo-op)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Applied Research Intern, Proactive Intelligence & Customer World Models (PhD / Graduate Co-op) at Block. Skills: Representation Learning, Foundation Models, Reinforcement Learning, Agentic Systems. Frame research problems. Develop research methods”
What You'll Achieve.
Ship production systems; Publish work in same year
Industry & Context.
Reasoning over customer state; Make better decisions; Learn continuously from outcomes
What They're Looking For.
Must Have
MS or PhD program enrollment, Foundations in modern machine learning, Experience conducting independent research, Fluency in Python, Experience with PyTorch, JAX, or similar frameworks, Evidence of research excellence
Nice to Have
Experience with large language models, Experience with agentic systems, Experience with reinforcement learning, Experience with reward modeling, Experience with 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
What You'll Do.
Frame research problems
Develop research methods
Run research experiments
Publish research findings
Ship work into production systems
Build customer world models
Develop proactive intelligence systems
Build agentic decision systems
Develop learning from feedback loops
Build evaluation frameworks
Full Job Description
Team: Apollo — Block Applied R&D Location: Remote (US / Canada) Duration: Fall/Winter 2026 co-op — 8 months, flexible start September 2026 Level: Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads Block's efforts to build the Customer World Model (CWM): a continuously evolving representation of each customer's goals, context, history, constraints, and likely future needs. The CWM powers proactive intelligence across Block's ecosystem. Instead of customers navigating products in search of features, intelligence observes their world, understands what matters, anticipates what comes next, and initiates actions on their behalf. We believe the next generation of AI products will not be defined by chat interfaces or isolated agents. They will be defined by rich world models that enable systems to reason over a customer's evolving state, make better decisions, and learn continuously from outcomes. Apollo designs, prototypes, and guides the development of this intelligence layer. About the role We're hiring a small cohort of graduate research interns to help build the foundations of proactive intelligence. This is not a traditional internship. 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. You'll work at the intersection of representation learning, foundation models, reinforcement learning, causal reasoning, agentic systems, and product intelligence. The goal is not simply to build smarter models, but to build systems that develop a deeper understanding of customers and use that understanding to make better decisions over time. Past interns have shipped production systems within months and published their work in the same year. What you'll work on Depending on your interests and Apollo's roadmap, you'll focus on one or more of the following are
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