Machine Learning Engineer Intern, Trust and Safety Engineering - 2027 Start (PhD)

Machine Learning Engineer Intern, Trust and Safety Engineering - 2027 Start (PhD) at TikTok in Sydney, Australia.

Responsibilities

Team Introduction

Building a world where people can safely discover, create and connect. The Trust & Safety (T&S) team at TikTok helps ensure that our global online community is safe and empowered to create and enjoy content across all of our applications. We have invested heavily in human and machine-based moderation to remove harmful content quickly and often before it reaches our general community.

• We are looking for talented individuals to join us for an internship in November/December 2026. Internships at our Company aim to offer students industry exposure and hands-on experience. Watch your ambitions become reality as your inspiration brings infinite opportunities at our Company.
• Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to Our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
• Successful candidates must be able to commit to the following Internships

1. From December 2026 - February 2027 (onboard by 7 Dec 2026)

As a Machine Learning Engineer, you'll have the chance to work with our clients and teams to address key business problems and identify areas of growth for the company. With your education and experience, you will be able to take on real-world challenges from day one.

1. Build industry-leading content safety systems for TikTok;
2. Develop highly-scalable classifiers, tools, models and algorithms leveraging cutting-edge machine learning, computer vision and data mining technologies;
3. Understand product objectives and improve trust and safety strategy and model's performance;
4. Work with cross-functional teams to protect TikTok globally.

Requirements

• Currently pursuing a PhD in Computer Science, engineering or quantitative field;
• Solid experience in at least one of the following areas: machine learning, pattern recognition, NLP, data mining, or computer vision;

Preferred Qualifications

• Experience in recommendation, search, advertising, or other related projects;
• Published papers in the top AI conferences or journals is a plus, including KDD, IJCAI, WWW, WSDM, ICML, NeurIPS, CVPR, ECCV, ICCV, ACL, etc.;
• Competition experience in machine learning, data mining, CV, NLP, etc.;
• Good understanding of data structures and algorithms;
• Passion for techniques and solving challenging problems.
• By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy
• If you have any questions, please reach out to us at apac-earlycareers@tiktok.com

About the Company

The Global Business Solutions (GBS) team is responsible for the revenue growth of the TikTok business, and our teams include Sales, Marketing, Ops, Account Managers, Agency and partnerships, as well as Marketing Science.

At TikTok, our Global Business Solutions (GBS) team plays a key role in generating revenue by promoting our advertising solutions, onboarding new clients, driving ad campaigns, and more. As the TikTok community grows at an unprecedented speed around the world, our GBS team leads groundbreaking projects that are changing the landscape of the advertising industry in real time.

We're seeking an analytically driven, and detail-oriented Client Solutions Manager (CSM) Intern to join our Ecommerce Team. As a CSM, you will partner closely with Client Partners and Client Solutions Managers to drive revenue by identifying opportunities, leveraging data insights, and delivering consultative solutions for advertisers.

This role centers on client education, relationship growth, data analysis, and campaign success. You will provide strategic recommendations to both clients and internal teams, ensuring campaigns achieve business objectives while optimizing long-term partnerships. Success in this role requires strong data analytics skills, adaptability in a fast-paced environment, and a test-and-learn mindset to uncover the best solutions.