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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in modern machine learning techniques, including deep learning and reinforcement learning, while effectively translating research into practical applications that enhance customer experiences. Proficient in building and evaluating AI systems that leverage customer data for proactive intelligence.
Highest-signal resume keywords
Machine LearningDeep LearningReinforcement LearningPython ProgrammingResearch Excellence
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Representation LearningFoundation ModelsOptimizationCausal ReasoningAgentic SystemsReward ModelingSequential Decision-MakingLarge Language ModelsGraph Data ProcessingEvaluation Frameworks
Soft Skills
CollaborationIndependent Research
Tools & Technologies
PyTorchJAXLarge-Scale ML Systems
Industry Keywords
Customer World ModelProactive IntelligenceBehavioral DataOperational SignalsEvent Streams
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- 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
Benefits
Comp & perks- 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