Machine Learning Engineer Graduate (Ads Targeting) - 2026 Start (BS/MS)
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About this role
The Ads Targeting's goal is to help advertisers reach their desired audience and optimize advertisement performance. As a member of the Ads Targeting, Ads Core team, you will apply machine learning models to scale budgets by understanding user interest and intention, and build large-scale foundations for data processing and serving for next-generation ad targeting products. This team is working on a variety of products such as custom audience, interest, behavior, lookalike, auto targeting etc., as well as new innovative features.
We are looking for talented individuals to join our team in 2026. 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 TikTok. Successful candidates must be able to commit to an onboarding date by end of year 2026. 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 TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities:
- Responsible for the development of state-of-the-art applied machine learning projects.
- Own key targeting components or strategies in the Tiktok ads monetization ecosystem.
- Build scalable platforms and pipelines for ads targeting products.
- Work with product and business teams on the product vision.
Minimum Qualifications:
- BS/MS degree in Computer Science, Statistics, Operation Research, Applied Mathematics, Physics or similar quantitative fields.
- Experience in one or more of the following areas: machine learning, deep learning, statistical models and applied mathematical methods.
- Strong coding skills, especially in Python/C++/Go. Experience with high-load systems.
- Familiarity with online experimentation and analytics.
- Familiarity with big data systems including Hadoop and Spark.
- Curiosity towards new technologies and entrepreneurship.
Preferred Qualifications:
- Experience in reinforcement learning, transfer learning, and counter-factual optimization is a plus.
- Experience with user modeling using deep learning methods from large scale datasets. Experience with privacy preserving modeling techniques is a plus.
- Experience in developing modern ads ranking/retrieval/targeting systems and recommender systems.