Internship – Machine Learning Ads

Job Description

Machine Learning Engineer Intern (Commerce Ads) – 2026 Summer (BS/MS) | TikTok

The Tone:
This is an internship at TikTok, for a role that may involve in-person work at one of the company’s global offices, as indicated by potential housing allowances. TikTok is a leading destination for short-form mobile video, dedicated to inspiring creativity and bringing joy to its global user base. This role directly supports the Commerce Ads team, which focuses on enhancing both open-loop and closed-loop commerce advertisements. The team’s mission is to establish TikTok as an essential growth engine for businesses of all sizes and a top destination for consumers to discover and buy products, content, and services. The work of this intern will be crucial for driving TikTok’s ad revenue and developing the next generation of web ad solutions for the platform.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: Multiple locations available, potentially in-person
• Pay: $45–$60 hourly
• Team: Commerce Ads team
• Mission: Enhance commerce ads on TikTok to drive business growth and establish it as a consumer shopping destination.
• Tech Stack: Go, C/C++, Python, TensorFlow, PyTorch, MXNet, Spark, Linux

What You’ll Actually Do
• Systems Development: Build highly scalable machine learning systems and state-of-the-art models to improve ads ranking quality and optimize advertiser strategies.
• Feature Improvement: Explore, develop, and experiment with new features to enhance model accuracy.
• Platform Optimization: Apply modern machine learning to improve ads relevance, quality, and quantity delivered to end-users, aligning with platform objectives.
• Cross-functional Collaboration: Partner with Product Managers, Designers, and other disciplines to explore and define the next generation of shopping experiences on TikTok.

The Must-Haves
• Background: Currently pursuing an Undergraduate or Master’s degree in Computer Science, Computer Engineering, or a closely related technical discipline. Possess a strong theoretical grounding in machine learning and deep learning concepts and techniques, including CNN, RNN, and LSTM architectures. Essential knowledge and skills in statistics are also required.
• Experience: Familiarity with basic data structures and algorithms is essential.
• Skills: Solid programming proficiency in languages such as Go, C/C++, and Python. Demonstrated analytical thinking capabilities. Familiarity with the Linux development environment. Candidates must also be familiar with the architecture and implementation mechanisms of at least one mainstream machine learning programming framework, such as TensorFlow, PyTorch, or MXNet.
• Bonus: A good understanding in one of the following domains: ads bidding & auction, ads quality control, or online advertising systems (familiarity with terms like CPC/CPM, CTR/CVR, Ranking/Targeting, Conversion/Budget, Campaign/Creative, Demand/Inventory, DSP/RTB). Experience in resource management and task scheduling with large-scale distributed software, specifically Spark and TensorFlow. Relevant work or research experiences in search and recommendation systems.