Training / AI Infrastructure
Genesis
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- Location
- United Kingdom
- Area
- Outside Africa — visa sponsorship — Outside Africa, visa sponsorship offered
- Contract
- Full Time
- Field
- Engineering & Research
- Published on
- 2 November 2026
- Closing date
- Not provided
Information not provided by the source
duration, work arrangement, salary, reference
Source: Arbeitnow · verified on 4 November 2026 at 21:01 (Paris time) · location given by the source: London
In brief
Parrainage de visa proposé (visa sponsorship available) selon Arbeitnow.
Description
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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Parrainage de visa proposé (visa sponsorship available) selon Arbeitnow.