Lead ML Scientist, Recommender Systems

TikTok Inc.; San Jose (CA); On-site; USD 162,000 - 317,000; Full time

Job summary

TikTok Inc. is seeking talented researchers to join the Recommendation organization. You will work on production recommendation models, drive product impact, and help scale infrastructure to improve user experience and platform growth.

The team is fast-paced and collaborative. Successful candidates will have the opportunity to contribute to major AI research areas, publish work, and align with product strategies in 2026, with onboarding by the end of the year.

Qualifications

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

Responsibilities

• 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.

Skills

Research experience

Cross-functional collaboration

Problem solving

Education

PhD in Computer Science/Engineering or related

Tools

PyTorch

TensorFlow

C/C++

Python

Shell scripting

Job description

TikTok Inc. is seeking talented researchers to join the Recommendation organization. You will work on production recommendation models, drive product impact, and help scale infrastructure to improve user experience and platform growth.

The team is fast-paced and collaborative. Successful candidates will have the opportunity to contribute to major AI research areas, publish work, and align with product strategies in 2026, with onboarding by the end of the year.