Training / AI Infrastructure

Genesis·Paris·Remote·Posted 30 April 2026

Apply with a tailored CV View on Genesis's site

About the role

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…

This is a summary of the advert. The full description and the application are on Genesis's careers site.

Apply faster with Prepper

A version of your CV tailored to this Training / AI Infrastructure role.
A cover letter written from your CV and this advert.
Prepper can fill in Genesis's application form and send it once you approve.
The application saved in your tracker, with reminders to follow up.

Start free

More roles at Genesis

Prepper is independent and not affiliated with Genesis. Roles are listed from the employer's public careers system and removed when they close.