Software Engineer Project Intern (Model Infrastructure) - 2026 Start (BS/MS)

TikTok; San Jose (CA); On-site; USD 51,143 - 72,840; Full time

Benefits offered by this job

Health insurance

Life insurance

Well-being benefits

10 paid holidays per year

Paid sick time

Job summary

A leading social media platform in California is seeking a Software Engineering Intern for the Model Infra team. The role involves optimizing recommendation systems, working on generative AI model integration, and driving hardware efficiency. Candidates should be pursuing a degree in Software Development or a related field, have strong programming skills in C++ and Python, and possess knowledge of computer architecture. Interns receive competitive hourly compensation starting at $45, benefits including health insurance, and paid holidays.

Qualifications

• Currently pursuing an Undergraduate/Master in a relevant technical discipline.
• Strong programming skills in C++ and Python.
• Solid understanding of Computer Architecture and the GPU software stack.
• Experience with deep learning frameworks and eager to investigate model execution.

Responsibilities

• Drive optimization of training and inference pipelines.
• Architect specialized systems for LLM integration.
• Build high-concurrency engines for Petabyte-scale streaming.
• Collaborate with researchers on next-generation recommendation architectures.
• Innovate on storage and synchronization of massive model states.

Skills

Strong programming skills in C++

Strong programming skills in Python

Solid understanding of Computer Architecture

Understanding of GPU software stack (CUDA)

Experience with deep learning frameworks (PyTorch, TensorFlow)

Education

Undergraduate/Master in Software Development, Computer Science, Computer Engineering

Job description

About the Team

The TikTok Model Infrastructure team is the core engine powering the world’s most engaged "For You" feed. We focus on the engineering efficiency and architectural evolution of recommendation models at an unprecedented scale. As we lead the industry’s shift toward LLM2Rec and Large Recommendation Models (LRM), our mission is to build ultra-high-performance infrastructure that bridges the gap between massive data scale and extreme algorithmic complexity.

We tackle the industry's most demanding "frontier" challenges: managing Petabyte-scale distributed embedding states, optimizing thousand-node GPU clusters, and perfecting real-time Sparse/Dense streaming. Our work ensures that models with hundreds of billions of dense parameters—on par with the world's largest LLMs—can operate with millisecond-level latency.

We are seeking Software Engineering Interns to join the Model Infra team to redefine the performance boundaries of recommendation systems. In this role, you will focus on the efficiency of the entire model lifecycle, work on the convergence of generative AI and recommendation architecture, and optimize everything from raw throughput of multi-billion parameter dense blocks to efficient retrieval of sparse features across massive distributed memory fabrics.

Responsibilities

• Drive the optimization of training and inference pipelines to maximize hardware utilization (MFU/HFU) for models featuring hundreds of billions of dense parameters.
• Architect specialized systems to support the integration of LLMs into the recommendation stack, focusing on memory‑efficient attention mechanisms and advanced KV cache management for long‑sequence user modeling.
• Build and optimize high‑concurrency engines for Petabyte‑scale streaming training, handling continuous parameter updates and high‑frequency data ingestion without compromising stability.
• Work closely with researchers to design next‑generation recommendation architectures optimized for modern GPU/NPU interconnects, ensuring high‑bandwidth utilization across the cluster.
• Innovate on how we store and synchronize massive model states across heterogeneous memory hierarchies (HBM, DDR, and NVMe).

Minimum Qualifications

• Currently pursuing an Undergraduate/Master in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Strong programming skills in C++ and Python.
• Solid understanding of Computer Architecture and the GPU software stack (CUDA, Triton, or NCCL).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and a desire to "look under the hood" of model execution runtimes.
• A strong interest in solving system‑level bottlenecks in large‑scale distributed environments.

Preferred Qualifications

• Experience with Transformer‑based architectures, 3D parallelism (TP/PP/DP).
• Deep understanding of the torch.compile stack, including TorchDynamo (graph acquisition) and TorchInductor (lowering).
• Hands‑on experience writing high‑performance kernels or optimizing collective communication (e.g., customizing NCCL/UCX).
• Familiarity with RDMA networking, high‑performance storage, or specialized Parameter Server architectures.
• Success in programming competitions (ACM‑ICPC) or contributions to prominent open‑source AI infrastructure or high‑performance computing projects.

Job Information

Compensation Description (Hourly) - Campus Intern

The hourly rate range for this position in the selected city is $45-$45.

Benefits

Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance. The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

• Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
• Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems;
• Exercising sound judgment.

For more information on reasonable accommodation: https://tinyurl.com/RA-request