Machine Learning Engineer Intern
TikTok USDS Joint Venture
This job at a glance
- Who can apply
- New grads and up to 1 year · Bachelor's degree or Master's degree
- Must know
- Social mediaMachine learningStakeholder managementPythonC++Deep learning
- Nice to have
- LLMs
- Work
- Remote · internship
- Pay
- Not stated by the employer.
- Skill demand
- Python76%Machine learning66%Stakeholder management25%Social media1%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 1, 2026 · still open
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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. We are looking for talented individuals to join us for an internship.
Internship Program Overview
Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth. Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals. Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.
Key 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.
Requirements & Tech Stack
- 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 a 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.
Intern 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).
- Potential eligibility for a housing allowance (if not working 100% remote).