(General Hire) Machine Learning Scientist Graduate (TikTok Recommendation) - 2026 Start (PhD)

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.

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 our Company.

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.

Responsibilities

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

Qualifications

Minimum Qualifications

1. Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
2. Good knowledge of theoretical and empirical research in addressing research problems
3. Solid knowledge and experience with at least one popular deep learning framework (e.g., PyTorch,TensorFlow) and familiarity with deep neural network architectures

Preferred Qualifications

1. Research experience in one or more of the following fields: applied machine learning, machine learning infrastructure, large-scale recommendation system, market-facing machine learning product.
2. Strong first-author publications record in major AI conferences or journals(e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL etc.)
3. Proficient in C/C++, Python, and shell programming languages, and have a deep understanding of data structure and algorithm design.
4. Internship experience in an AI research organization