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Software Engineer Project Intern (Model Infrastructure) - 2026 Start (BS/MS)
San Jose, California · Internship · Posted Oct 28, 2026
- Education
- Currently pursuing an undergraduate or master’s degree in a related technical discipline.
About the job
Develop infrastructure that improves the performance and efficiency of large-scale recommendation model training, inference, and state management.
What you'll do
- Optimize training and inference pipelines for hardware utilization.
- Build systems for integrating LLMs into recommendations, including memory-efficient attention and KV cache management.
- Develop high-concurrency streaming and distributed model-state systems, and co-design architectures for GPU/NPU clusters.
What they ask for
- Currently pursuing an undergraduate or master’s degree 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, such as CUDA, Triton, or NCCL.
- Experience with deep learning frameworks such as PyTorch or TensorFlow.
Nice to have
- Experience with Transformer architectures, 3D parallelism, torch.compile, high-performance kernels or collective communication, RDMA, high-performance storage, or Parameter Server architectures.
- Programming competition success or contributions to open-source AI infrastructure or high-performance computing projects.
Tools
C++, Python, CUDA, Triton, NCCL, PyTorch, TensorFlow, TorchDynamo
AI focus
Build and optimize infrastructure for LLM-integrated recommendation systems and large recommendation models, including training, inference, attention, KV caching, and distributed model state.
Model-written summary · the original posting is authoritative