ML Engineer Intern – Recommendation Systems (Summer 2027)

TikTok; San Jose (CA); On-site; USD 51,000 - 73,000; Full time

Benefits offered by this job

Health insurance

Paid holidays

Housing allowance

Job summary

TikTok in San Jose is seeking a Machine Learning Engineer Intern for Summer 2027 in the Recommendation group. You will join a fast-paced team working on production recommendation models and end-to-end ML pipelines to drive product impact.

Responsibilities include developing state-of-the-art recommendation solutions, collaborating with researchers and engineers, and gaining hands-on experience across model design, data processing, and system infrastructure during a 12-week internship.

Qualifications

• Currently pursuing a Master degree with a background in computer science, machine learning, or similar fields.
• 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.
• Able to commit to working for 12 weeks during Summer 2027.

Responsibilities

• Drive the development of industry-leading recommendation systems that elevate user experience and platform growth.
• Deliver impactful, end-to-end machine learning solutions tackling product challenges related to content understanding, LLMs, robustness, and fairness.
• Own and optimize the full-stack ML pipeline—from algorithm design to system infrastructure.
• Collaborate with cross-functional teams to craft innovative product strategies and develop intelligent solutions for TikTok's growth.

Skills

Machine learning

Deep learning

Research ability

Python

Shell scripting

Education

Master's degree in CS/ML

Tools

PyTorch

TensorFlow

C/C++

Python

Job description

TikTok in San Jose is seeking a Machine Learning Engineer Intern for Summer 2027 in the Recommendation group. You will join a fast-paced team working on production recommendation models and end-to-end ML pipelines to drive product impact.

Responsibilities include developing state-of-the-art recommendation solutions, collaborating with researchers and engineers, and gaining hands-on experience across model design, data processing, and system infrastructure during a 12-week internship.