About the role#
This internship focuses on the infrastructure that powers recommendation systems and Large Language Models. You will work on distributed training, high-performance GPU computing, and scalable AI infrastructure. The team builds core systems that support billions of personalized recommendations and advances foundation model training. You will collaborate with researchers and engineers to move AI technologies into production.
What you'll do#
- Build and optimize infrastructure for large-scale model training and online inference.
- Develop distributed systems that support 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.
What you'll need#
- Currently pursuing a Bachelor's or Master's degree in Computer Science or a related field.
- Strong programming skills in C++ or Python.
- Understanding of data structures, algorithms, and computer systems.
- Familiarity with PyTorch or TensorFlow.
- Knowledge of Transformer architectures and Large Language Models.
- Experience with GPU programming using CUDA or Triton is a plus.
- Familiarity with distributed training concepts like DP, TP, PP, FSDP, or ZeRO.
- Understanding of LLM serving techniques such as KV Cache, Continuous Batching, or FlashAttention.
- Hands-on experience with LLM training or inference through research, internships, or open-source projects.
Location & details#
- Location: San Jose, California.
- Term: Summer 2027.
- Modality: On-site.
- Employment: Full-time internship.
- Compensation: $45 per hour.
About TikTok
TikTok operates as an entertainment provider. The company maintains a global presence with offices in cities including Los Angeles, Singapore, New York, London, and Tokyo. It employs over 92,000 people. The organization is privately held.
How to get in at TikTok
Landing an internship at TikTok requires speed because early applicants often get seen before the pile grows. Intern Insider sends an instant alert the moment a role matching your target is published anywhere, so you can apply among the first. This gives you a better chance of your resume being reviewed while the team is still actively filling the position. You should aim to be one of the first people to submit your materials. Reaching out to the right person can also improve your chances of getting a response. Intern Insider surfaces the recruiters behind the company roles so you can contact them directly to ask about the role or a referral. This direct approach often works better than waiting for a response from a general application queue.
