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Machine Learning Engineer Intern - Global E-commerce Risk Control - PhD

ByteDance

Salary not specified
Aug 27, 2025
Seattle, WA, USA
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To protect Bytedance e-commerce users and make Bytedance e-commerce the safest and most trusted place worldwide to transact online by securing the integrity of the e-commerce ecosystem and providing a safe shopping experience on the platform

Requirements

  • Proficiency in modern machine learning theories and applications, including ensemble trees, deep neural networks, transfer/multi-task learning, reinforcement learning, graph theory, and unsupervised learning.
  • Experience with Python, SQL/Hive, and Hadoop
  • Strong understanding of data structures and algorithms, with excellent problem-solving ability
  • Demonstrated software engineering experience from previous internship, work experience, coding competitions, or publications
  • Internship experience or research experience, especially in e-commerce, risk control domain

Responsibilities

  • Develop and implement innovative machine learning algorithms to manage business risks in Bytedance 's products and platforms.
  • Prototype and explore novel solutions, conduct experiments to validate hypotheses, and provide insights to Product and Tech teams.
  • Collaborate with multidisciplinary teams to enhance current automation processes.
  • Build efficient data querying infrastructure for real-time and offline analysis. Identify opportunities to strengthen risk defense solutions.
  • Define risk control metrics and promote data-driven practices. Align teams and stakeholders on numeric goals for risk control.
  • Document technical processes and effectively communicate results through writing, visualizations, and presentations.

Other

  • Currently pursuing a PhD in Computer Science Engineering, Operations Research, or related fields.
  • Able to commit to working for 12 weeks during Summer 2026
  • Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
  • Detail oriented, effective time management, and strong analytical skills
  • Graduating December 2026 onwards with the intent to return to degree program after the completion of the internship.