E-Commerce Risk Control Machine Learning Intern (PhD, Summer 2026) – Machine Learning

Job Description

Machine Learning Engineer Intern (Global E-commerce Risk Control) – 2026 Start (PhD) | ByteDance

The Tone:
This is an internship at ByteDance, a global technology company founded in 2012, whose mission is to inspire creativity and enrich life. The company creates over a dozen products, including TikTok, Lemon8, CapCut, Pico, Toutiao, Douyin, and Xigua, to help people connect with, consume, and create content. The E-Commerce Risk Control (ECRC) team ensures the safety and trustworthiness of ByteDance’s e-commerce platforms. This role is crucial for protecting users, preventing malicious activities, and maintaining the integrity of the e-commerce ecosystem by developing and implementing advanced machine learning solutions.

The TL;DR
• Role: Internship
• Type: Full-time (12 weeks)
• Location: Not specified (US-based likely, with potential for Los Angeles County)
• Pay: $57 hourly
• Team: E-Commerce Risk Control (ECRC) team
• Mission: To develop and implement machine learning solutions to manage business risks in ByteDance’s e-commerce products and platforms.
• Tech Stack: Python, SQL/Hive, Hadoop

What You’ll Actually Do
• Development: Develop and implement machine learning algorithms to manage business risks in ByteDance’s products and platforms.
• Exploration: Prototype and explore novel solutions, conduct experiments to validate hypotheses, and provide insights to Product and Tech teams.
• Collaboration: Collaborate with multidisciplinary teams to enhance current automation processes.
• Infrastructure: Build efficient data querying infrastructure for real-time and offline analysis and identify opportunities to strengthen risk defense solutions.
• Metrics & Communication: Define risk control metrics, promote data-driven practices, align teams on numeric goals, and effectively communicate technical results.

The Must-Haves
• Background: Currently pursuing a PhD in Computer Science Engineering, Operations Research, or related fields.
• Experience: Able to commit to working for 12 weeks during Summer 2026. 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.
• Skills: Strong understanding of data structures and algorithms, excellent problem-solving ability, detail-oriented, effective time management, and strong analytical skills.
• Bonus: Demonstrated software engineering experience from previous internship, work experience, coding competitions, or publications. Internship or research experience, especially in e-commerce or risk control domain. Curiosity towards new technologies and quick problem-solving capabilities.