Minimum Qualifications
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related technical fields
- Experience using or developing open source frameworks for LLM inference such as vLLM or SGLang.
Proficient in at least one deep learning framework (e.g., PyTorch, Megatron, DeepSpeed, JAX), with experience in model inference workflows
- Understanding of modern computing systems, including hardware, storage, and networking, and how they impact ML workloads
- Familiarity with compilers or model optimization pipelines (e.g., PyTorch Dynamo), or related model execution workflows
- Able to commit to working for 12 weeks in 2026
Preferred Qualifications
- Experience with distributed or large-scale ML systems, including training or inference pipelines and related optimizations (e.g., FSDP, DeepSpeed, Megatron, GSPMD)
- Experience with GPU/TPU/NPU programming and performance optimization, or high-performance computing and communication (e.g., CUDA, Triton, NCCL, RDMA)
- Understanding of AI compiler and model optimization stacks (e.g., torch.fx, PyTorch Dynamo, XLA, MLIR)