(General Hire)Machine Learning Engineer Graduate (TikTok Recommendation) - 2025 Start (Master)

San Jose, California, United States

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Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact. The team is fast-pacing, collaborative and impact-driven.

This opening is part of the general hiring process for the TikTok Recommendation organization. Applications will be evaluated by multiple teams within the Recommendation organization to ensure the best fit based on skills and interests.

Responsibilities - What You'II Do
- Build industry-leading recommendation system, improving user experience, content ecosystem and platform security;
- Deliver end-to-end machine learning solution to address critical product challenges;
- Own the full stack machine learning system and optimize algorithms and infrastructure to improve recommendation performance.
- Work with cross functional teams to design product strategies and build solutions to grow TikTok in important markets.

We are looking for talented individuals to join our team in 2025. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.

We will prioritize candidates who are able to commit to these start dates. Please state your availability and graduation date clearly in your resume.

Applications will be reviewed on a rolling basis. We encourage you to apply early.

Candidates can apply for a maximum of TWO positions and will be considered for jobs in the order you applied for. The application limit is applicable to TikTok and its affiliates' jobs globally.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  2  0  0

Tags: Machine Learning Security

Perks/benefits: Career development

Region: North America
Country: United States

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