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$161,250–$254,750.
Based on 240 similar postings.
Employer
About Block
Block, Inc. (formerly Square) is a financial technology company operating the Square merchant payments ecosystem, Cash App peer-to-peer payments, TIDAL music streaming, and Bitcoin-focused financial services. Industry: Financial Technology & Payments
Block currently has
53 open roles
on FindRole.
Listed pay typically runs
$217,800–$326,800
across 52 roles with salary data.
Careers - Applied Research Intern, Proactive Intelligence & Customer World Models (PhD / Graduate Co-op) joins the Apollo team to develop foundational components for proactive intelligence. This role involves owning research problems end-to-end, from framing questions and developing methods to running experiments and shipping results into production systems. The work focuses on building Customer World Models by creating representations of customer goals and history through event-based foundation models, memory architectures, and multi-modal data. Key projects include developing agentic decision systems for autonomous workflow execution, reinforcement learning for reward modeling, and evaluation frameworks for safety and reliability. Candidates must possess strong foundations in deep learning, optimization, and representation learning while demonstrating proficiency in Python with PyTorch or JAX. The role addresses the challenge of creating systems that reason over evolving customer states to anticipate needs and initiate actions automatically.
Own research problems end-to-end by framing questions, developing methods, running experiments, and publishing findings.
Build representation models of customers using event streams, financial activity, and behavioral data.
Develop proactive intelligence systems to anticipate customer needs and initiate actions automatically.
Create agentic decision systems that perform multi-step reasoning and autonomous workflow execution.
Implement reinforcement learning methods to improve system performance based on real-world feedback loops.
Build evaluation frameworks to measure decision quality, safety, and reliability in simulated environments.
Translate research findings into production-ready code for use by millions of customers.
What we're looking for
Must be currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field.
Must be returning to the graduate program after the completion of the co-op.
Must have strong foundations in deep learning, optimization, representation learning, and foundation models.
Must have experience conducting independent research and translating ideas into working systems.
Must be fluent in Python with experience using PyTorch, JAX, or similar frameworks.
Must demonstrate research excellence through publications, open-source contributions, technical leadership, or equivalent work.
Preferred experience with large language models and agentic systems.
Preferred experience with reinforcement learning, reward modeling, or sequential decision-making.
Python
SQL
R
Java
Data Engineering
Data Science
Kubernetes
PowerBI
Azure
AKS
Snowflake
Oracle
SQL Server
Database Design
Data Modeling
Data Visualization
Predictive Modeling
Machine Learning
PyTorch
TensorFlow
Jax
Recommendation Systems
Graph Modeling
Multi-GPU
Multi-node
Google Cloud
AWS
Azure
Data Processing
Information Retrieval