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Salary
≈ $165k – $370k per year (Estimated)
Location
In office (San Jose)
Seniority
Junior
Visa
H-1B filings in 12 months: 547 · for this role: 328 · green card filings: 242
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 3, 2026. First seen by Alion on Aug 3, 2026. TikTok scores B on the Alion truth index.

Overview
Company
Impact
Profile match
TikTok is a short-form video platform owned by the Chinese technology group ByteDance and launched internationally in 2016, growing further after the 2018 merger with the lip-sync app Musical.ly. Its recommendation feed surfaces content by engagement signals rather than social graph, which lets new creators reach large audiences quickly and made the app one of the most downloaded in the world. The company runs dual operating hubs in Singapore and Los Angeles and has built an advertising business, a live streaming economy and the TikTok Shop commerce marketplace on top of the video feed.

岗位职责 / Responsibilities

The TikTok Commerce Ads team is dedicated to blending advertiser focus with technical expertise. Our mission is to enhance commerce ads-both open-loop and closed-loop-to establish TikTok as an essential growth engine for businesses of all sizes and a top destination for consumers to discover and buy products, content, and services. We are crucial to driving TikTok's ad revenue and are committed to developing the next-generation web ad solutions for the platform.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year. 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.

Responsibilities:

- Build highly scalable machine learning systems and state-of-the-art machine learning models to improve ads ranking quality and optimize advertisers' marketing strategies. Examples include but are not limited to click through rate prediction, conversion rate prediction, intelligent format selection and user journey optimization.

- Explore, develop and experiment with new features to improve model accuracy.

- Understand ads platform objectives and take full advantage of modern machine learning to improve ads relevance, quality, and quantity delivered to end-users.

- Collaborate with Product Managers, Designers, and other disciplines to explore the next generation of shopping experiences on TikTok.

任职要求 / Requirements

Minimum Qualifications:

- Individuals who are completing or have recently completed a Bachelor's or above degree in Computer Science, Computer Engineering, or a related technical discipline.

- Solid programming skills, including but not limited to: Go, C/C++, Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.

- Good analytical thinking capability. Have essential knowledge and skills in statistics.

- Good theoretical grounding in the machine and deep learning concepts and techniques (CNN/RNN/LSTM, etc.).

- Familiar with the architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet), familiar with its architecture and implementation mechanism.

Preferred Qualifications:

- Good understanding in one of the following domains: ads bidding & auction, ads quality control, and online advertising systems (familiar with one or more of these terms: CPC/CPM, CTR/CVR, Ranking /Targeting, Conversion/Budget, Campaign/Creative, Demand/Inventory, DSP/RTB).

- Experience in resource management and task scheduling with large-scale distributed software (such as Spark and TensorFlow).

- Relevant work or research experiences in search and recommendation.

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