Algorithm Engineer Project Intern (TikTok Live Revenue) - 2027 start - Project Intern (TikTok Global LIVE) - 2027 Start
- Sydney, Australia
- Internship
- Intern/New Grad
- Posted
Skills
Required
- Software Development
Preferred
- LIVE
- algorithms
- machine learning
- provide algorithmic support
- deep learning
At the same time, each business scenario needs technical solutions built for its own demands. You will work alongside a strong team on problems that move real product metrics and user experience, where every line of code you write reaches hundreds of millions of users.
About TikTok
R&D team builds and maintains the products behind TikTok's live streaming business.
Our work spans social interaction, monetization activities, the creator ecosystem, subscription services, game streaming, and guild and operations platforms, supporting the product's rapid growth in global markets.
Behind those products sit hard technical problems in service architecture, large model algorithms, and foundation technologies.
Solving them keeps a fast-growing business reliable, efficient, and secure.
TikTok Live revenue engineering team is responsible for building the cutting-edge revenue ecosystem which includes gifting and other revenue features that are innovative, secure and intuitive for our users.
As an important member of the engineering team, you will build solutions that affect millions of users and live streamers.
We are looking for talented individuals to join our team in 2027.
As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Launch your career where inspiration is infinite at our Company.
Watch your ambitions become reality as your inspiration brings infinite opportunities at our Company.
As a Machine Learning Engineer / Scientist, you will work on algorithmic solutions that support large-scale LIVE activities for users around the world.
You will apply your research background and machine learning expertise to solve real-world business challenges, optimize activity performance, and drive sustainable business growth.
Responsibilities
- Build and optimize machine learning systems that provide algorithmic support for global large-scale LIVE activities. - Analyze activity data, develop strategy models, and use data-driven approaches to improve user engagement and business growth. - Design, train, and deploy scalable models and algorithms to support activity recommendation, ranking, targeting, and performance optimization. - Understand business objectives and work closely with product and operations teams to define long-term algorithm strategies and roadmap. - Collaborate with cross-functional teams to continuously improve model performance, experimentation efficiency, and business impact.
- Minimum Qualifications 1.
- Solid knowledge in at least one of the following areas: machine learning, deep learning, LLM, agent, causal inference.
- 3.
- Familiar with the at least one of the data-centric domains: recommendation, generation, ab testing.
- Proven passion about solving real problems.
- 2.
- Basic knowledge about algorithm developement, deployment and serving.
- 3.
- 4.
- Trackable academic achievement in recent 3 years.
Requirements
- Currently pursuing an Undergraduate in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
- Great communication skill and ownership.
- Preferred Qualifications 1.
- Previous experience in tech companies as the related role.
Successful candidates must be able to commit to an onboarding date by end of year 2027. Please state your availability and graduation date clearly in your resume. 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. 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.
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