Machine Learning Engineer Intern (Risk & Integrity) - 2027 Summer

About the role

The USDS Platform and Community Integrity (PaCI) team is the architectural backbone of TikTok's Risk & Integrity in the US. We drive end-to-end integrity for TikTok and its expanding ecosystem, including Lemon8 and emerging affiliate platforms, by leveraging localized US data and state-of-the-art AI/LLM capabilities. USDS Joint Venture LLC is dedicated to the safety and security of millions of Americans who create, discover, and connect with what they love on the apps we operate. The Joint Venture has been established in compliance with the Executive Order signed by President Trump on September 25, 2025. Our foundation is a comprehensive data privacy and cybersecurity program we operate under defined safeguards to protect national security and secure U.S. user data, apps and the algorithm. We safeguard the U.S. content ecosystem, holding decision-making authority for trust and safety policies and moderation. USDS Joint Venture helps ensure Americans can continue to express their creativity, discover new hobbies and interests, and build thriving communities and businesses on a global scale. On-site presence across teams allows the company to operate with greater speed, alignment, and agility — especially in areas like real-time decision-making, team development, and integrated execution. As such, the company is shifting from a hybrid work model to a fully in-person schedule up to 5 days a week.

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.

Qualifications

Minimum Qualification(s):

• 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 foundation in Machine Learning; proficient in applying Transformer and GNN architectures to solve large-scale integrity challenges with social graph and behavior sequence data.
• Experience designing model evaluation systems that balance technical performance with product goals.
• Strong engineering and coding skills.
• Proficient in at least one language among Python, C++, or Go; familiar with distributed computing (e.g., Spark, Flink) and deep learning frameworks (e.g., PyTorch).

Preferred Qualifications:

• Currently pursuing an Master's degree in Computer Science, Computer Engineering, Software Engineering, or a related technical discipline.
• Agentic AI Experience: Hands-on experience building LLM-based Agents capable of task planning, tool-use, or closed-loop autonomous decision-making.
• LLM Security & Alignment: Experience in LLM Post-training or Fine-tuning (e.g., SFT, RLVR, RLHF) to optimize models for specific risk domains like fraud intent recognition or malicious redirection.
• Multimodal Expertise: Proven track record in video understanding or multimodal representation; ability to integrate visual, audio, and textual features to solve complex behavioral modeling challenges.

Benefits

• Day‑one access to health insurance, life insurance, wellbeing benefits and more.
• 10 paid holidays per year.
• Paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year).
• Housing allowance for interns not working 100% remote.

Pay

Hourly rate range: $45‑$45.

Schedule

• 12‑week internship during Summer 2027.
• Fully in‑person schedule up to 5 days a week (shift from hybrid model).