ML Engineer Intern, Risk & Integrity — AI/LLM Systems

TikTok USDS Joint Venture

San Jose (CA)

On-site

USD 51,000 - 73,000

Full time

7 days ago
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Benefits offered by this job

Health insurance
Housing allowance
Wellbeing benefits
Life insurance

Job summary

TikTok USDS Joint Venture LLC is offering a 12-week internship on the PaCI platform, focusing on end-to-end integrity for TikTok and affiliated platforms. You will work with large-scale data, collaborate with engineering, data science, and ML teams, and write clear code and documentation throughout the project lifecycle.

The program emphasizes practical ML, Transformer/GNN applications, and real-world challenges in risk and integrity, providing mentorship, workshops, and social learning events.

Qualifications

  • Currently pursuing a Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related technical field.
  • Able to commit to a 12-week internship during Summer 2027.
  • Solid ML foundation; experience with Transformer and GNN architectures on large-scale data.
  • Strong coding skills in Python, C++, or Go; familiarity with Spark, Flink, and PyTorch.

Responsibilities

  • Work with large-scale data, logs, metrics, or experiments to understand user search behavior and improve product or system quality.
  • Collaborate with engineering, product, data science, and machine learning partners to define requirements and deliver project milestones.
  • Write clear, maintainable code and documentation for assigned workstreams.
  • Communicate progress, risks, and learnings with mentors and stakeholders throughout the internship.

Skills

Machine Learning
Python
C++
Go
Spark
Flink
PyTorch
Transformer models
GNN

Education

Bachelor's degree in Computer Science
Master's degree in Computer Science

Tools

Spark
Flink
PyTorch

Job description

TikTok USDS Joint Venture LLC is offering a 12-week internship on the PaCI platform, focusing on end-to-end integrity for TikTok and affiliated platforms. You will work with large-scale data, collaborate with engineering, data science, and ML teams, and write clear code and documentation throughout the project lifecycle.

The program emphasizes practical ML, Transformer/GNN applications, and real-world challenges in risk and integrity, providing mentorship, workshops, and social learning events.

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