Spring/Summer 2027 PhD Large Language Model Engineer Co-op
San Jose, CA$91.5kUNAVAILABLEPosted 2w ago
About the role
PhD-level co-op internship at AMD focusing on scalable training and inference of large language models, ML systems, HPC, and AI infrastructure. Onsite full-time role in San Jose, CA for Spring/Summer 2027 with opportunities to publish and collaborate across research and engineering teams.
Responsibilities
- Conduct research on scalable training and inference of large language models, focusing on ML systems and HPC techniques
- Develop and optimize distributed training frameworks, model parallelism strategies, and efficient resource management for large-scale AI workloads.
- Explore hardware-aware optimizations, including algorithm-hardware co-optimization, sparsity-aware computation, quantization, and memory-efficient techniques for LLMs.
- Implement and benchmark state-of-the-art ML system optimizations, leveraging high-performance computing techniques.
- Collaborate with researchers and engineers to publish findings in top-tier conferences (NeurIPS, ICML, MLSys, SC, etc.).
Qualifications
- Currently pursuing a PhD in Computer Science, Electrical Engineering, or a related field with a focus on ML Systems, HPC, or AI Infrastructure.
- Strong background in machine learning, distributed systems, and parallel computing.
- Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, JAX) and large-scale model training.
- Proficiency in Python and C++, with experience in performance profiling and optimization.
- Knowledge of GPUs, ASICs, distributed training paradigms (e.g., data/model pipeline parallelism, FSDP, ZeRO, DeepSpeed, Megatron-LM).
- Familiarity with HPC techniques, including MPI, Rcom/CUDA, RCCL/NCCL, and high-speed networking technologies.
- Prior research experience in scalable deep learning systems, large-scale LLM training, or AI acceleration.
- Experience with AI compiler optimizations (e.g., Triton, XLA, MLIR).
Skills
Required:Large language model (LLM) training and inferenceDistributed training frameworksHardware-aware optimizationsProgramming languages
Nice to have:AI compiler optimizations
Benefits
- AMD benefits at a glance (link provided in description)
Last updated Oct 15, 2026. Interested? Apply on the company site.
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