ML Infra Engineer Intern (Ads Infra) - 2027 Summer
Responsibilities
The ads system at TikTok operates on a massive scale and serves millions of advertisers, clients and influencers across the world. The quality of the ads system highly depends on the ability to handle massive data, and machine learning is widely used to improve the quality of our ads. The Ads Infra team is responsible for building highly efficient and stable infrastructure to collect and process data for the usage of machine learning training, serving, and privacy enforcement, including feature engineering, feature store, training data generation, etc.
We are looking for talented individuals to join us for an internship. 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.
Want more jobs like this?
Get Software Engineering jobs in San Jose, CA delivered to your inbox every week.
Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.
Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted.
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:
- Develop and optimize advertising recommendation models, covering training, evaluation, inference and user behavior sequence modeling.
- Build large-scale data pipelines for sample generation and joining, feature processing, storage and data quality assurance.
- Develop ML platforms for distributed training, model distribution, online serving and lifecycle management.
- Explore MLLM applications in advertising, including data production, model training, fine-tuning and inference optimization.
- Apply AI agents to workflow orchestration, resource scheduling, failure diagnosis and automated operations.
- Build machine learning platforms for GPU allocation, scheduling, usage metering, cost accounting and utilization optimization.
Qualifications
Minimum Qualifications:
- Currently pursuing a Bachelor's/ Master's in Computer Science, AI, Machine Learning or a related discipline.
- Proficiency in at least one programming language, such as C++, Python, Go or Java.
- Solid knowledge of data structures, algorithms, machine learning and computer systems.
- Familiarity with recommendation systems, MLLMs, distributed systems, ML platforms or large-scale data processing.
- Experience with deep learning frameworks, distributed training, GPU scheduling, AI agents or cloud-native technologies is a plus.
By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy
Perks and Benefits
Health and Wellness
- Health Insurance
- Dental Insurance
- Vision Insurance
- HSA
- Life Insurance
- Fitness Subsidies
- Short-Term Disability
- Long-Term Disability
- On-Site Gym
- Mental Health Benefits
- Virtual Fitness Classes
Parental Benefits
- Fertility Benefits
- Adoption Assistance Program
- Family Support Resources
Work Flexibility
- Flexible Work Hours
- Hybrid Work Opportunities
Office Life and Perks
- Casual Dress
- Snacks
- Pet-friendly Office
- Happy Hours
- Some Meals Provided
- Company Outings
- On-Site Cafeteria
- Holiday Events
Vacation and Time Off
- Paid Vacation
- Paid Holidays
- Personal/Sick Days
- Leave of Absence
Financial and Retirement
- 401(K) With Company Matching
- Performance Bonus
- Company Equity
Professional Development
- Promote From Within
- Access to Online Courses
- Leadership Training Program
- Associate or Rotational Training Program
- Mentor Program
Diversity and Inclusion
- Diversity, Equity, and Inclusion Program
- Employee Resource Groups (ERG)
Company Videos
Hear directly from employees about what it is like to work at TikTok.