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TikTok · 2 weeks ago

Machine Learning Engineer Intern (Monetization Technology - Ads Creative) - 2026 Start (BS/MS)

United States

Internship

Remote

Intern

$45/hr - $60/hr

Start in 2026 Spring

TikTok is the leading destination for short-form mobile video, and they are seeking a Machine Learning Engineer Intern for their Monetization Technology team. The role focuses on enhancing ad creative understanding and optimization through innovative tech solutions, providing hands-on experience in a dynamic environment.

Content CreatorsContent DiscoveryMedia and EntertainmentSocial MediaVideo

H1B Sponsor Likely

Responsibilities

Assist in utilizing algorithms to better understand advertisers, creators, and creatives, improving precision in match-making processes

Contribute to online modeling of large-scale commercial traffic, optimizing the distribution strategy of creatives within the recommendation and ads systems

Help develop allocation strategies for both natural and ads traffic, aimed at increasing both short-term and long-term value for advertisers and creators

Collaborate with senior engineers to implement and test new algorithms that enhance the accuracy of content recommendations

Participate in analyzing large datasets to identify trends and patterns, providing actionable insights for improving the ad targeting strategy

Support the development of performance metrics to track the effectiveness of ad and creative distribution strategies

Conduct experiments to validate new algorithms and strategies, ensuring scalability and efficiency in production systems

Contribute to continuous optimization of machine learning models for better performance across diverse traffic and creative data

Assist in preparing and presenting reports on model performance and recommendations to stakeholders

Qualification

Machine LearningRecommendation SystemsData StructuresProgramming (Python/C++)Deep LearningLarge-scale Data ProcessingA/B TestingCommunicationTeam CollaborationProblem Solving

Required

Currently pursuing a Bachelor's degree or higher in Computer Science or a related field

Research/internship experience or coursework in machine learning (e.g., RecSys, NLP, CV, GE), with a preference for candidates with exposure to recommendation systems

Solid understanding of data structures and algorithms, with proficiency in at least one programming language (e.g., Python, C++, Golang)

Strong interest in exploring new technologies, with a demonstrated ability to analyze problems and find solutions

Good communication skills, with an eagerness to collaborate within a team and learn from peers

Strong enthusiasm for contributing to business growth and willingness to take on challenges in a dynamic environment

Preferred

Previous internship or research experience in machine learning/deep learning, with a focus on recommendation systems, or advanced ranking solution strategies like RAG/LoRA/MoE etc

Familiarity with large-scale data processing and distributed systems

Exposure to reinforcement learning or deep learning techniques for optimizing recommendation systems

Knowledge of A/B testing and other experimental design techniques to evaluate algorithm performance

Strong interest in content personalization and ad optimization technologies

Experience with model deployment or working in production environments

Benefits

Interns have day one access to health insurance

Life insurance

Wellbeing benefits and more.

Interns also receive 10 paid holidays per year

Paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year).

Interns who are not working 100% remote may also be eligible for housing allowance.

Company

TikTok

Glassdoor3.4

TikTok is a short-form video entertainment app and social network platform. It is a sub-organization of ByteDance.

Founded in 2003

Los Angeles, California, USA

10001+ employees

https://www.tiktok.com

H1B Sponsorship

TikTok has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

Represents job field similar to this job

Trends of Total Sponsorships

2025 (979)

2024 (601)

2023 (387)

2022 (322)

2021 (133)

2020 (72)