GPU/AI Application System Software Engineer Intern (System Technologies and Engineering) - 2026 Summer (BS/MS)

Job Description:

The GPU/AI System Technology and Engineering Team is committed to developing highly optimized OS and system software to support deep learning and high-performance computing (HPC) workloads in large-scale data centers. We focus on delivering core software components for the next generation of AI and HPC platforms, benchmarks, and fine-tuning performance. Our work spans the entire hardware/software stack, from GPU drivers to deep learning frameworks, to ensure peak performance across all layers. By joining this team, you will work with the best engineers and talents in this industry and have a broad opportunity to get in touch with the latest AI application systems and newly emerged technology in computing, networking and storage. You will gain remarkable GPU architecture, system software development and GPU validation experience in the most advanced hardware infrastructure on a massive scale. We are looking for talented individuals to join us for an internship in 2026. Internships at TikTok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at TikTok. Internships at TikTok aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth. This Internship Program runs for 12 weeks beginning in May/June 2026. Successful candidates must be able to commit to one of the following internship start dates below: (Select below options for Summer) - 5/11/2026 - 5/18/2026 - 5/26/2026 - 6/8/2026 - 6/22/2026 We will prioritize candidates who are able to commit to these start dates. Please state your availability clearly in your resume (Start date, End date). 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 TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities: - Design and implement performance benchmarks and testing methodologies to evaluate system performance - Develop benchmark tools and performance optimization of AI workloads specifically tailored for large-scale LLM training and inference, as well as High-Performance Computing (HPC). - Develop Python scripts to automate the testing of various benchmark tools. - Collaborate with internal teams to identify system bottleneck, debug and improve performance issues

Candidate Requirements:

Minimum Qualifications: - Must be able to commit to a 12-week full-time work period during Summer 2026 - Currently pursuing a Bachelor's, Master's, or PhD degree within Computer Engineering in Electrical Engineering, Computer Engineering, Computer Science or related majors. - Background with GPU/CPU benchmarking - Familiar with ML/DL techniques, algorithms and frameworks like TensorFlow or PyTorch. - Exposure to testing automation for various applications. - Proficiency in Python and C/C++ - Hands-on experience with Linux based systems - Ability to work independently and complete projects from beginning to end and in a timely manner Preferred Qualifications - Strong background in one of the following fields: High Performance Computing, ML Hardware Acceleration (e.g., GPU/TPU/RDMA) or ML for Systems, and Distributed Storage. - Experience in AI model development, training, evaluation and deployment on Cloud, Cluster or on-premises. - Experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM) - Experience with development applications with CUDA programming - Linux kernel development experience, such as networking and device drivers etc. - Familiar with git workflow. - Exposure to testing automation for various applications. - Experience with complex system-level debugging is invaluable