Applied Research Intern, Proactive Intelligence & Customer World Models (PhD / Graduate Co-op)
Block · CA
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About the Role
We are hiring a small cohort of graduate research interns to help build the foundations of proactive intelligence. This is not a traditional internship; you will own a research problem end-to-end, from framing the question to shipping your work into production systems used by millions. You'll work at the intersection of representation learning, foundation models, reinforcement learning, causal reasoning, agentic systems, and product intelligence, aiming to build systems that deeply understand customers and make better decisions over time.
Responsibilities
- Own a research problem end-to-end: framing the question, developing methods, running experiments, publishing findings, and shipping work into production systems.
- Focus on one or more of the following areas: Customer World Models, Proactive Intelligence, Agentic Decision Systems, Learning from Feedback Loops, Evaluation and Measurement.
- Build rich representations of customers from event streams, financial activity, operational signals, and behavioral data.
- Develop systems that can anticipate customer needs and initiate helpful actions.
- Build agents that reason over customer world models and take actions in real environments.
- Develop methods for intelligence to improve continuously from real-world outcomes.
- Build evaluation frameworks that predict real-world performance, trust, and customer value.
Requirements
- 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.
- Experience with large language models and agentic systems (nice to have).
- Experience with reinforcement learning, reward modeling, or sequential decision-making (nice to have).
- Experience with representation learning for structured, temporal, or graph data (nice to have).
- Familiarity with large-scale training and production ML systems (nice to have).
- Interest in building AI systems that directly affect customer outcomes (nice to have).
Skills
- Python
- PyTorch
- JAX
- Deep Learning
- Optimization
- Representation Learning
- Foundation Models
- Large Language Models
- Agentic Systems
- Reinforcement Learning
- Reward Modeling
- Sequential Decision-Making
- Structured Data
- Temporal Data
- Graph Data
- Large-scale Training
- Production ML Systems
Location
- Remote (US / Canada)
Work Type
- Co-op
- Internship
- Remote
Experience Level
- Graduate student (MS or PhD)
Education Level
- MS or PhD program
Benefits
- Remote work
- Medical insurance
- Flexible time off
- Retirement savings plans
- Modern family planning
About the Company
- Block, Inc. (NYSE: XYZ) builds technology to increase access to the global economy. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone.