Machine Learning Intern – Ads Creative Optimization

Job Description

Machine Learning Engineer Intern (Monetization Technology – Ads Creative) | TikTok

The Tone:
This is an internship at TikTok, located in Los Angeles, CA. TikTok is a leading destination for short-form mobile video, aiming to inspire creativity and bring joy globally. This role is crucial within the Ads Creative & Ecosystem team, which focuses on developing technology solutions for understanding, producing, and optimizing ad creatives and landing pages. The intern’s work directly contributes to TikTok’s core monetization efforts by enhancing advertising effectiveness and user experience.

The TL;DR
• Role: Internship
• Type: Seasonal, Temporary
• Location: In-person, Los Angeles, CA
• Pay: $45–$60 hourly
• Team: Ads Creative & Ecosystem team
• Mission: Solve the challenge of producing effective and scalable ad creatives through tech solutions for understanding, generation, and optimization.
• Tech Stack: Python, C++, Golang, RecSys, NLP, CV, GE, RAG, LoRA, MoE

What You’ll Actually Do
• Algorithm Application: Assist in leveraging algorithms to deeply understand advertisers, creators, and creatives, thereby improving the precision of matchmaking processes.
• System Optimization: Contribute to online modeling of large-scale commercial traffic, aiming to optimize the distribution strategy of creatives within recommendation and ads systems.
• Strategy Development: Help develop allocation strategies for both natural and ads traffic to increase both short-term and long-term value for advertisers and creators.
• Recommendation Enhancement: Collaborate with senior engineers to implement and test new algorithms that enhance the accuracy of content recommendations.
• Performance Analysis: Participate in analyzing large datasets to identify trends and patterns, providing actionable insights for improving ad targeting strategies and tracking effectiveness.

The Must-Haves
• Background: Currently pursuing a Bachelor’s degree or higher in Computer Science or a related field, with coursework or experience in machine learning.
• Experience: Prior research or internship experience in machine learning, particularly with exposure to recommendation systems.
• Skills: Solid understanding of data structures and algorithms, proficiency in Python, C++, or Golang, and strong problem-solving and communication abilities.
• Bonus: Previous internship or research focusing on recommendation systems or advanced ranking solutions (like RAG/LoRA/MoE), familiarity with large-scale data processing, distributed systems, reinforcement learning, A/B testing, or experience in production environments.