Machine Learning Engineer Intern (Payment Data Intelligence) - 2027 Summer

About the team

The USDS Payment team at TikTok builds the core payment capabilities supporting a smooth, secure, and reliable payment experience across the platform — spanning payment acquisition, disbursement, transaction monitoring, payment method management, FX conversion, accounting, and reconciliation.

Within this org, the Payment Data Intelligence team applies data science and machine learning to improve payment services at scale. The team leverages large-scale datasets and advanced algorithms to power business-critical use cases including financial risk control, payment compliance, user growth, and operational optimization — at the intersection of ML, data infrastructure, and real-world fintech challenges.

This internship focuses on building agent-first AI applications for payment scenarios. The role is designed for candidates who want to apply the latest AI paradigms, including LLM-based agents, workflow orchestration, prompt engineering, MCP-based tool integration, and AI application evaluation, to solve practical payment business problems.

We are looking for talented individuals to join us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth.

Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.

Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.

Responsibilities

• Work with product, strategy, engineering teams to design, develop, and deploy ML solutions for payment-related business problems
• Translate business needs into data-driven and algorithmic approaches
• Contribute to use cases such as fraud detection, risk modeling, user experience optimization, and campaign effectiveness
• Participate in data processing and feature engineering workflows at scale
• Experiment with ML models and improve components of the model lifecycle (data labeling, feature systems, model robustness, automation)
• Explore advanced AI techniques (deep neural networks, LLMs) in payment intelligence scenarios

Minimum Qualification(s)

• Currently pursuing a Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related technical field.
• Able to commit to a 12-week internship during Summer 2027.
• Strong foundation in machine learning, data analysis, and programming
• Proficient in large-scale data tools: SQL, Hive, or Spark
• Proficient in Python, Java, or Scala

Preferred Qualification(s)

• Strong analytical thinking and problem-solving ability
• Experience in ML, risk modeling, recommendation systems, trust & safety, or fintech
• Familiarity with deep learning or LLM applications