AI Infrastructure Engineer Graduate (TikTok Recommendation Architecture) - 2027 Start
Responsibilities
Team Introduction
Our team develops the core training and serving infrastructure that powers one of the world's largest recommendation systems, enabling billions of personalized recommendations every day. We are also advancing the next generation of AI infrastructure for foundation models and LLMs, driving innovation in large-scale model training, online inference, and GPU optimization.
As part of the team, you will work on distributed training and inference systems, high-performance GPU computing, and scalable LLM infrastructure. You'll collaborate closely with experienced engineers and researchers to transform cutting-edge AI technologies into production systems that directly impact the experience of hundreds of millions of TikTok users. This role is ideal for candidates who are passionate about LLM systems, distributed computing, GPU programming, and building AI systems at massive scale. We are looking for passionate New Graduates to join our Model Infrastructure team, building the next generation of infrastructure for TikTok's For You recommendation system and Large Language Models (LLMs).
We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
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Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities
- Build and optimize infrastructure for large-scale model training and online inference.
- Develop distributed systems supporting large recommendation models and LLMs.
- Improve training and inference performance through GPU optimization and efficient communication.
- Collaborate with researchers to develop and deploy LLM training and serving solutions.
- Analyze system bottlenecks and implement performance optimizations.
Qualifications
Minimum Qualifications:
- Individuals who are completing or have recently completed a Bachelor's or Master's degree in Artificial Intelligence, Software Development, Computer Science, Computer Engineering or a related discipline.
- Strong programming skills in C++ or Python.
- Good understanding of data structures, algorithms, and computer systems.
- Familiarity with PyTorch or TensorFlow.
- Knowledge of Transformer architectures and Large Language Models (LLMs).
- Strong problem-solving skills and a passion for building large-scale AI systems.
Preferred Qualifications:
- Hands-on experience with LLM training or inference through research, internships, or open-source projects.
- Familiarity with distributed training concepts (e.g., DP, TP, PP, FSDP, ZeRO).
- Experience with GPU programming using CUDA, Triton, or similar technologies.
- Understanding of LLM serving techniques such as KV Cache, Continuous Batching, or FlashAttention.
- Contributions to open-source projects or research in machine learning systems, distributed systems, or LLM infrastructure.
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.