Training / AI Infrastructure
Genesis
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- Local
- Reino Unido
- Zona
- Fora de África — patrocínio de visto — Fora de África, patrocínio de visto proposto
- Contrato
- Full Time
- Área
- Engineering & Research
- Publicada em
- 2 Novembro 2026
- Data de encerramento
- Não indicado
Informações não fornecidas pela fonte
duração, modalidade de trabalho, salário, referência
Fonte: Arbeitnow · verificada em 4 Novembro 2026 às 21:01 (hora de Paris) · local indicado pela fonte: London
Em resumo
Parrainage de visa proposé (visa sponsorship available) selon Arbeitnow.
Descrição
What You’ll Do
Drive down wall-clock time to convergence by profiling and eliminating bottlenecks across the foundation model training stack stack, from data pipelines to GPU kernels
Design, build, and optimize distributed training systems (PyTorch) for multi-node GPU clusters, ensuring scalability, robustness, and high utilization
Implement efficient low-level code (CUDA, cuDNN, Triton, custom kernels) and integrate it seamlessly into high-level training frameworks
Optimize workloads for hardware efficiency: CPU/GPU compute balance, memory management, data throughput, and networking
Develop monitoring and debugging tools for large-scale runs, enabling rapid diagnosis of performance regressions and failures
What You’ll Bring
Deep experience in distributed systems, ML infrastructure, or high-performance computing (8+ years)
Production-grade expertise in Python
Low-level performance mastery: CUDA/cuDNN/Triton, CPU–GPU interactions, data movement, and kernel optimization
Scaling at the frontier: experience with PyTorch and training jobs using data, context, pipeline, and model parallelism
System-level mindset with a track record of tuning hardware–software interactions for maximum utilization
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