Machine Learning Intern – E-commerce Risk Control

Job Description

Machine Learning Engineer Intern (Global E-commerce Risk Control) – 2026 Summer (BS/MS) | ByteDance

The Tone:
This is a 12-week internship at ByteDance, a company founded in 2012 that builds a suite of more than a dozen products including TikTok, Lemon8, CapCut, Pico, Toutiao, Douyin, and Xigua, with a mission to inspire creativity and enrich life. This role is crucial for the E-commerce Risk Control (ECRC) team, whose mission is to protect ByteDance’s e-commerce users, including buyers, sellers, and creators. The team aims to establish ByteDance e-commerce as the safest and most trusted global platform by securing the integrity of its ecosystem and providing a safe shopping experience for all.

The TL;DR
• Role: Internship
• Type: Temporary
• Location: Undisclosed
• Pay: $57.75 hourly
• Team: E-commerce Risk Control (ECRC) team
• Mission: To prevent and detect risk attempts across ByteDance e-commerce platforms and mitigate their negative impact on customers and Selling Partners.
• Tech Stack: Python, SQL/Hive, Hadoop

What You’ll Actually Do
• Develop: Implement innovative machine learning algorithms to manage various business risks within ByteDance’s products and platforms.
• Prototype: Explore novel solutions, conduct experiments to validate hypotheses, and provide data-driven insights to Product and Tech teams.
• Collaborate: Work with multidisciplinary teams to enhance existing automation processes and improve overall risk control measures.
• Build: Construct efficient data querying infrastructure for both real-time and offline analysis, identifying opportunities to strengthen risk defense solutions.
• Define & Communicate: Establish clear risk control metrics, promote data-driven practices across teams, align stakeholders on numeric goals, and document technical processes and results effectively through various mediums.

The Must-Haves
• Background: Currently pursuing a BS/MS degree in Computer Science Engineering, Operations Research, or related fields.
• Experience: Ability to commit to working for 12 weeks during Summer 2026. Demonstrated proficiency in modern machine learning theories and their applications, including ensemble trees, deep neural networks, transfer/multi-task learning, reinforcement learning, graph theory, and unsupervised learning.
• Skills: Strong command of Python, SQL/Hive, and Hadoop. Excellent understanding of data structures and algorithms, coupled with strong problem-solving capabilities. Exhibited detail-orientation, effective time management, and robust analytical skills.
• Bonus: Prior software engineering experience from previous internships, work experience, coding competitions, or publications. Research or internship experience, particularly within the e-commerce or risk control domains. A high degree of curiosity towards new technologies and an entrepreneurial mindset, alongside strong creativity and quick problem-solving abilities.