Operate and optimize large-scale LLM pre-training on 1,000+ GPU clusters using PyTorch, DeepSpeed, or Megatron-LM. Improve networking (InfiniBand/RDMA), memory management, checkpointing, and failure recovery. Manage SLURM/Kubernetes GPU clusters and apply systems engineering (C++, CUDA, Python) and 3D parallelism techniques.
We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing distributed infrastructure. The ideal candidate will have a deep understanding of GPU clusters and extensive experience in system engineering to ensure efficient and reliable training processes.
Responsibilities:
- Orchestrate distributed training runs across 1,000+ GPUs using PyTorch, DeepSpeed, or Megatron-LM.
- Optimize networking (InfiniBand/RDMA) and memory management to prevent out-of-memory errors.
- Automate checkpointing and failure recovery during month-long training runs.
Required Skills:
- Deep expertise in 3D parallelism (Data, Tensor, Pipeline).
- Experience managing SLURM or Kubernetes-based GPU clusters.
- Strong systems engineering background (C++, CUDA, Python).
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Ranked among the hottest tech cities in 2024 by CompTIA, Charlotte is quickly cementing its place as a major U.S. tech hub. Home to more than 90,000 tech workers, the city’s ecosystem is primed for continued growth, fueled by billions in annual funding from heavyweights like Microsoft and RevTech Labs, which has created thousands of fintech jobs and made the city a go-to for tech pros looking for their next big opportunity.
Key Facts About Charlotte Tech
- Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
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- Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
- Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus

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