About the role
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).
Skills & Tags
Aplyr's read
Hyphen Connect is a tech innovator in connectivity solutions, employing diverse roles from risk management to marketing, with a strong focus on Mandarin speakers.
What's promising
- •Hyphen Connect is at the forefront of connectivity technology innovation.
- •The company offers diverse roles, from risk management to tech consultancy.
- •Opportunities for Mandarin speakers are abundant, indicating a focus on Asian markets.
What to watch
- •High demand for Mandarin speakers may limit opportunities for non-speakers.
- •The company appears to have a high turnover in compliance roles.
- •Limited public information about company culture and work-life balance.
Why Hyphen Connect
- •Hyphen Connect bridges traditional and decentralized finance roles.
- •The company emphasizes roles in both tech and financial compliance sectors.
- •Focus on Mandarin-speaking roles suggests strategic alignment with Asian markets.
Aplyr’s read is generated by AI from public sources. Was it useful?
About Hyphen Connect
Hyphen Connect is a technology company focused on providing innovative solutions for connectivity and communication in various industries.
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