Machine Learning Engineer Intern

Job Description

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

The Tone:
This is an internship at TikTok, likely based in a US city such as Los Angeles, where the company’s global headquarters are located. TikTok builds a leading platform for short-form mobile video, aiming to inspire creativity and bring joy. This role on the Commerce Ads team is critical to blending advertiser focus with technical expertise, enhancing commerce ads to establish TikTok as an essential growth engine for businesses and a top destination for consumers to discover and buy products. This position is crucial for driving TikTok’s ad revenue and developing next-generation web ad solutions.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: In-person, Los Angeles, CA
• Pay: $45–$60 hourly
• Team: TikTok Commerce Ads team
• Mission: To enhance commerce ads to make TikTok an essential growth engine for businesses and a top destination for consumers to discover and buy products.
• Tech Stack: Go, C/C++, Python, Linux development environment, TensorFlow, PyTorch, MXNet, Spark

What You’ll Actually Do
• System Building: Build highly scalable machine learning systems and models to improve ads ranking quality and optimize advertisers’ marketing strategies.
• Feature Development: Explore, develop, and experiment with new features to improve model accuracy.
• Objective Alignment: Understand ads platform objectives and apply modern machine learning to improve ads relevance, quality, and quantity delivered to end-users.
• Cross-functional Collaboration: Collaborate with Product Managers, Designers, and other disciplines to explore 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 related technical discipline.
• Experience: Ability to commit to a 12-week full-time work period during Summer 2026.
• Skills: Solid programming skills in Go, C/C++, or Python; familiarity with basic data structures and algorithms; familiarity with Linux development environment; good analytical thinking capability; essential knowledge and skills in statistics; good theoretical grounding in machine and deep learning concepts and techniques (e.g., CNN, RNN, LSTM); familiarity with the architecture and implementation of at least one mainstream machine learning programming framework (e.g., TensorFlow, PyTorch, MXNet).
• Bonus: Good understanding in one of the following domains: ads bidding & auction, ads quality control, and online advertising systems (e.g., 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 (such as Spark and TensorFlow); relevant work or research experiences in search and recommendation.